master thesis topics embedded systems

Embedded Systems Research Topics Ideas

List of Research Topics and Ideas of Embedded Systems for MS and Ph.D. Thesis.

Embedded system design: embedded systems foundations of cyber-physical systems, and the internet of things
Jetset: Targeted firmware rehosting for embedded systems
Time-Sensitive Networking in automotive embedded systems: State of the art and research opportunities
SoK: Enabling Security Analyses of Embedded Systems via Rehosting
Digital for real: A multicase study on the digital transformation of companies in the embedded systems domain
CondenseNeXt: An Ultra-Efficient Deep Neural Network for Embedded Systems
Towards Tolerating Soft Errors for Embedded Systems
Energy consumption optimization of processor scheduling for real-time embedded systems under the constraints of sequential relationship and reliability
Reliability and availability prediction of embedded systems based on environment modeling and simulation
Exploring the software repositories of embedded systems: An industrial experience
A Generalization Performance Study Using Deep Learning Networks in Embedded Systems
A Service Discovery Solution for Edge Choreography-Based Distributed Embedded Systems
Probabilistic Estimation of Threat Intrusion in Embedded Systems for Runtime Detection
Application of Information Technologies and Programming Methods of Embedded Systems for Complex Intellectual Analysis
Singular Value Decomposition in Embedded Systems Based on ARM Cortex-M Architecture
The Design of a 2D Graphics Accelerator for Embedded Systems
A lightweight virtualization model to enable edge computing in deeply embedded systems
PIERES: A Playground for Network Interrupt Experiments on Real-Time Embedded Systems in the IoT
Analysis of the Capabilities of Embedded Systems in Intra Prediction Video Coding
Smart Car Features using Embedded Systems and IoT
Distributed Virtual Environment Basketball Equipment Embedded Systems’ Research and Development
Recent developments in code compression techniques for embedded systems
Power Clocks: Dynamic Multi-Clock Management for Embedded Systems
Porting and Execution of Anomalies Detection Models on Embedded Systems in IoT: Demo Abstract
Automated Driver Testing for Small Footprint Embedded Systems
Lane Compression: A Lightweight Lossless Compression Method for Machine Learning on Embedded Systems
A Low-Cost Implementation of Sample Entropy in Wearable Embedded Systems: An Example of Online Analysis for Sleep EEG
MOGATS: a multi-objective genetic algorithm-based task scheduling for heterogeneous embedded systems
Automatic identification and hardware implementation of a resource-constrained power model for embedded systems
Prototyping embedded systems for vibrodrivers monitoring
Incorporating On-going Verification & Validation Research to a Reliable Real-Time Embedded Systems Course
Development and Evaluation of Collaborative Embedded Systems using Simulation
Model-Based Engineering in the Embedded Systems Domain
Engineering of Collaborative Embedded Systems
Function Modeling for Collaborative Embedded Systems
An Application on Women Safety Using Embedded Systems and IoT
MPI hardware framework for many-core based embedded systems
Development of An Online PTT Voice Transmission System Between Cell Phones, Computers and Embedded Systems Over the Internet
Handling Uncertainty in Collaborative Embedded Systems Engineering
Dependable Software Generation and Execution on Embedded Systems
Creating Trust in Collaborative Embedded Systems
Language Engineering for Heterogeneous Collaborative Embedded Systems
Systematic Review of Methodologies for the Development of Embedded Systems
Automatic Vulnerability Detection in Embedded Devices and Firmware: Survey and Layered Taxonomies
Technical Foundations of Embedded Systems
Embedded Systems–A look into Optimized Energy Metering Devices
Contention-aware Adaptive Model Selection for Machine Vision in Embedded Systems
Dynamic Safety Certification for Collaborative Embedded Systems at Runtime
Power-Aware Fault-Tolerance for Embedded Systems
Implementazione di Deep Learning su sistemi embedded: The ALOHA experience= Implementation of Deep Learning on embedded systems: The ALOHA experience
An Embedded Systems Remote Course
… of a Real-Time Traffic Sign Recognition System Based On Deep Learning Approach with Convolutional Neural Networks and Integrating to The Embedded Systems
Towards Embedded Systems
Second Workshop on Next Generation Real-Time Embedded Systems
Low-cost Hardware-In-the-Loop (HIL) Simulator for Simulation and Analysis of Embedded Systems with non-real-time Applications
Soft Error Handling for Embedded Systems using Compiler-OS Interaction
Capability memory protection for embedded systems
Trusted Verification of Over-the-Air (OTA) Secure Software Updates on COTS Embedded Systems
Evaluation of physical education teaching based on web embedded system and virtual reality
IoT Based Real-Time Monitoring of Phytoremediation of Wastewater using the Mathematical Model Implemented on the Embedded Systems
Modifying Embedded Systems by Very-Fast Modules for Statistical Operations via SIMD
Research on Fintech development issues based on embedded cloud computing and big data analysis
Animal tumor medical image analysis based on image processing techniques and embedded system
A Review of Confidentiality Threats Against Embedded Neural Network Models
Remote embedded devices test framework on the cloud
Gravity: An Artificial Neural Network Compiler for Embedded Applications
Embedded System Learning Platform for Developing Economies
Smart Soldier Health Monitoring System Incorporating Embedded Electronics
Embedded Hardware System and Sensor Robot Used In Goal Tracking Technology Of Sports Football Goalkeeper
Finding Software Bugs in Embedded Devices
Everything You Always Wanted to Know About Embedded Trace
A Discreet Wearable Long-Range Emergency System Based on Embedded Machine Learning
Embedded Digital Control with Microcontrollers: Implementation with C and Python
Embedded Deep Learning Prototyping Approach for Cyber-Physical Systems: Smart LIDAR Case Study
Research on the HRM performance assessment model based on FPGA embedded system and bayesian network
Application of web embedded system and machine learning in english corpus vocabulary recognition
Codenet: Efficient deployment of input-adaptive object detection on embedded fpgas
HBONext: An Efficient Dnn for Light Edge Embedded Devices
Modeling cultures of the embedded software industry: feedback from the field
Hospital remote monitoring embedded system and nursing intervention for patients with anxiety and insomnia
Animation virtual reality scene modeling based on complex embedded system and FPGA
Strategy of library information resource construction based on FPGA and embedded system
Real-time systems
Construction of youth public sports service system based on embedded system and wireless IoT
Challenges in the Realm of Embedded Real-Time Image Processing
A Novel Rail-Network Hardware Simulator for Embedded System Programming
Analysis of cross-border E-Commerce logistics model based on embedded system and genetic algorithm
An embedded lightweight SSVEP-BCI electric wheelchair with hybrid stimulator
Applied Soft Computing and Embedded System Applications in Solar Energy
Advanced Systems Engineering
Demo abstract: Porting and execution of anomalies detection models on embedded systems in iot
Design of embedded digital image processing system based on ZYNQ
Action recognition of dance video learning based on embedded system and computer vision image
Research and Implementation of Embedded Database Encryption System based on Lightweight Cryptographic Algorithms
Model-Based Programming of Intelligent Embed-ded Systems and a Robotic Messenger to Mercury
A Novel, Model-Based, Specification-Driven Embedded Software Integration Platform
Event-B Hybridation: A Proof and Refinement-based Framework for Modelling Hybrid Systems
Analisi esaustiva di DAG task: soluzioni per moderni sistemi real-time embedded
Lossless Decompression Accelerator for Embedded Processor with GUI. Micromachines 2021, 12, 145
Introduction to the Special Issue on Specification and Design Languages (FDL 2019)
Case Study: ECHONET Lite Applications based on Embedded Component Systems
An interview study of how developers use execution logs in embedded software engineering
Static Allocation of Basic Blocks Based on Runtime and Memory Requirements in Embedded Real-Time Systems with Hierarchical Memory Layout
Magnetoresistive Circuits and Systems: Embedded Non-Volatile Memory to Crossbar Arrays
Intelligent hospital and traditional Chinese medicine treatment of cerebrovascular dementia based on embedded system
Implementation of Artificial Intelligence Algorithm In Embedded System
A state-of-the-art techno-economic review of distributed and embedded energy storage for energy systems
Intelligent medical diagnosis and misoprostol medical abortion nursing based on embedded system
Design of enterprise financial early warning model based on complex embedded system
SkiffOS: Minimal Cross-compiled Linux for Embedded Containers
Embedded, Edge and Cloud Computing for Gas Turbine Digital Twins
MASTER OF SCIENCE: ELECTRONIC SYSTEMS FOR EMBEDDED AND COMMUNICATING APPLICATIONS
Embedded Web Server for Hospital and Clinical Nursing Analysis of Cataract Anti-Inflammatory Drugs
Design of an Embedded System for Remote Monitoring of Malnutrition for People Living in Rural Areas
9 Comparison of Sensor-Embedded Closed-Loop Supply Chain Systems with Regular Systems
Time Synchronization Method for ARM-Based Distributed Embedded Linux Systems Using CCNT Register
An Experimental Design Approach to IoT Enabled Smart Parallel Irrigation System Using Embedded Microcontrollers
CNN-based Hand Gesture Recognition Method for Teleoperation Control of Industrial Robot
Efficient ROS-Compliant CPU-iGPU Communication on Embedded Platforms
Compression and Speed-up of Convolutional Neural Networks Through Dimensionality Reduction for Efficient Inference on Embedded Multiprocessor
Art Practice as Policy Practice: Framing the Work of Artists Embedded in Government
Architectures for Dynamically Coupled Systems
Design Space Exploration for Secure IoT Devices and Cyber-Physical Systems
Development of integrated spectral sun-photometer based on embedded Linux OS
Analysis of Risk Priority Number and Functionally Safe Design of Battery Management System
Performance Assessment of Linux Kernels with PREEMPT_RT on ARM-Based Embedded Devices
Exploration of word width and cluster size effects on tree-based embedded FPGA using an automation framework
Hardware acceleration of multibody simulations for real-time embedded applications
Remote music teaching classroom based on embedded system and cloud platform
Deployment of IoT for smart home application and embedded real-time control system
Machine learning and multiresolution decomposition for embedded applications to detect short-circuit in induction motors
Compact Groups of Galaxies in Sloan Digital Sky Survey and LAMOST Spectral Survey. II. Dynamical Properties of Isolated and Embedded Groups
A secure data parallel processing based embedded system for internet of things computer vision using field programmable gate array devices
Development of an Embedded Longitudinal Flight Control based on X-Plane Flight Simulator
Design of embedded acoustic image acquisition system for wireless sensor network
Health systems effects of successive emergency health and nutrition projects: an embedded retrospective case study analysis in Sudan and Pakistan
Efficient HLS implementation of fast linear discriminant analysis classifier
A Survey On Door Lock Security System Using IoT
Software Modeling and Analysis
Robust Computing for Machine Learning-Based Systems
DIALED: Data Integrity Attestation for Low-end Embedded Devices
Efficient Flash Indexing for Time Series Data on Memory-constrained Embedded Sensor Devices.
Future smart battery and management: Advanced sensing from external to embedded multi-dimensional measurement
Power System Frequency Adjustment Based on Embedded System and Internet of Things
Automatic Generation of Reconfiguration Blueprints for IMA Systems Using Reinforcement Learning
The design of embedded Operating System for vehicle Internet of Things
Embedded sensing package for temporary bone cement spacers in infected total knee arthroplasty
Social Distance Shopping Using Embedded Based Auto Cart and Android App
Which groups and designs are embedded in a dierence block design?
Embedded Linux Based Smart Secure IoT Intruder Alarm System Implemented on BeagleBone Black
Chapter Two-Hardware accelerator systems for embedded systems.
Benchmarking vision kernels and neural network inference accelerators on embedded platforms
Compositional Verification using Model Checking and Theorem Proving
Performative Practices and States of Play: Exploring the Role of Arts and Culture in the Co-Creation of Anticipatory Governance Dynamics
Design of Efficient Floating-Point Convolution Module for Embedded System
Prediction simulation of sports injury based on embedded system and neural network
Design of embedded system of volleyball training assistant decision support based on association rules
Implementation of a Hierarchical Embedded Cyber Attack Detection system for sUAS Flight Control Systems
IDRA: An In-storage Data Reorganization Accelerator for Multidimensional Databases
TRP: A Foundational Platform for High-Performance Low-Power Embedded Image Processing
A Certificate-Based Authentication for SIP in Embedded Devices
A Quantitative Study of Energy Consumption for Embedded Security
Runtime Monitoring on a Real-Time Embedded System
STHEM: Productive Implementation of High-Performance Embedded Image Processing Applications
Supporting the Creation of Digital Twins for CESs
Cross-level Co-simulation and Verification of an Automatic Transmission Control on Embedded Processor
Resident consumption expenditure forecast based on embedded system and machine learning
Fault Diagnose of DC Drive EV Utilizing a New Series Motor Four Quadrants DC Chopper Using an Expert System and Quadratic Solver Running in Embedded
LEG-PER-LiDAR-enhanced GNSS positioning error reduction
Low Voltage Low Power Output Programmable OCL-LDO with Embedded Voltage Reference
Second nearest-neighbor modified embedded-atom method interatomic potentials for the Mo-M (M= Al, Co, Cr, Fe, Ni, Ti) binary alloy systems
A Survey on Silk supply chain management using blockchain
Employment and Entrepreneurship Education for University Students Based On Improved ACO Algorithm and Embedded Database
Hardware Trojan Attack in Embedded Memory
A Survey on Garbage Management System
Modeling Computational Systems
Real-time, High-resolution Depth Upsampling on Embedded Accelerators
Communication Failure Resilient Improvement of Distributed Neural Network Partitioning and Inference Accuracy
Fiber optic sensor embedded smart helmet for real-time impact sensing and analysis through machine learning
A Novel Modeling-Attack Resilient Arbiter-PUF Design
Uncertainty-Aware Compositional System-Level Reliability Analysis
Optimization and Embedded Implementation of Gesture Recognition Algorithm Based on Convolutional Neural Network
A flexible tool for estimating applications performance and energy consumption through static analysis
Turtle-shell data embedding method with high image fidelity
Study of online learning resource recommendation based on improved BP neural network
Implementing a real-time image captioning service for scene identification using embedded system
Knowledge-Based Verification of Concatenative Programming Patterns Inspired by Natural Language for Resource-Constrained Embedded Devices
Designing of Arbiter PUF for Securing IP and IoT Devices
An embedded atom model for Ga–Pd systems: From intermetallic crystals to liquid alloys
Embedded IoT-based Monitoring Utility for Safety Management and Access Control
Improving saddle stitching line using affordable embedded system
CasCon: Cascaded Thermal And Electrical Current Throttling for Mobile Devices
SMT-based Contention-Free Task Mapping and Scheduling on SMART NoC
S-CNN-ESystem: An end-to-end embedded CNN inference system with low hardware cost and hardware-software time-balancing
Online fault diagnosis for smart machines embedded in Industry 4.0 manufacturing systems: A labeled Petri net-based approach
A Literature Survey on Wildlife Camera Trap Image processing using Machine Learning Techniques
EM Lifetime Constrained Optimization for Multi-Segment Power Grid Networks
Dynamic rocking response of “SDOF-embedded foundation” systems using shake table experiments
Comparing culturally embedded frames of judicial dispassion
Image enhancement in embedded devices for internet of things
A Review on Workload Characteristics for Multi Core Embedded Architectures using Machine Learning and Deep Learning Techniques
SoC-based embedded real-time simulation of mismatched photovoltaic strings
How to model Complex Systems?
Smart metering system data analytics platform using multicore edge computing
Ranking loss: Maximizing the success rate in deep learning side-channel analysis
Multi-Fidelity Digital Twins: a Means for Better Cyber-Physical Systems Testing?
A lightweight motional object behavior prediction system harnessing deep learning technology for embedded adas applications
Virtual simulation design and effect of high jump technology action optimization based on complex embedded system
Online Experiment-Driven Learning and Adaptation
RAP Model—Enabling Cross-Layer Analysis and Optimization for System-on-Chip Resilience
Concrete quantum cryptanalysis of binary elliptic curves
Research on Energy Saving and Emission Reduction Technology Based on Field Communication and Embedded Control Computer Data Exchange Algorithm
Efficient Embedded Cluster Density Approximation Calculations with an Orbital-Free Treatment of Environments
Modeling and Analyzing Context-Sensitive Changes during Runtime
… -sense: the exploration of the craft and material of fiberglass as a medium for tangible user interfaces. Towards the development of embedded circuits in fiberglass …
Development and assessment of a low-cost embedded system for evaluation of animal thermal comfort
Fault-Tolerant Computing with Heterogeneous Hardening Modes
Secure Mutual Authentication and Key-Exchange Protocol Between PUF-Embedded IoT Endpoints
Our Perspectives
A Pilot Study of Smart Agricultural Irrigation using Unmanned Aerial Vehicles and IoT-Based Cloud System
Tool Support for Co-Simulation-Based Analysis
Optical Waveguide Channel Routing with Reduced Bend-Loss for Photonic Integrated Circuits
ODAS: Open embedded audition system
A modified embedded-atom method interatomic potential for bismuth
ASTEROID and the Replica-Aware Co-scheduling for Mixed-Criticality
Enhancing Performance of Gabriel Graph-Based Classifiers by a Hardware Co-Processor for Embedded System Applications
Fixslicing AES-like Ciphers
CrESt Use Cases
Piezoelectric Sensor-Embedded Smart Rock for Damage Monitoring in a Prestressed Anchorage Zone
Task Sequencing in Frame-Based CPS
Operating Systems for Reconfigurable Computing: Concepts and Survey
Lightweight Software-Defined Error Correction for Memories
Design of Efficient, Dependable SoCs Based on a Cross-Layer-Reliability Approach with Emphasis on Wireless Communication as Application and DRAM …
Cross-Layer Resilience Against Soft Errors: Key Insights
Analysis of Power Adaptation Techniques Over Beaulieu-Xie Fading Model
Reliable CPS Design for Unreliable Hardware Platforms
Designing a high-speed light emitting diode driver circuit for visible light communications
Design, fabrication, and testing of a flexible three-dimensional printed percutaneous needle with embedded actuators
Variant and Product Line Co-Evolution
Convolutional Neural Network based Signal Classification in Real-Time
Increasing Reliability Using Adaptive Cross-Layer Techniques in DRPs: Just-Safe-Enough Responses to Reliability Threats
Using improved RFM model to classify consumer in big data environment
Enterprise financial risk management platform based on 5 G mobile communication and embedded system
Thermal Management and Communication Virtualization for Reliability Optimization in MPSoCs
[PS][PS] New Directions in Symbolic Model Checking for Real-Time Systems
A Wearable Embedded System for Assisting Cognition of Visually Impaired People by Street Scene Description
A 2.44 Tops/W Heterogeneous DCNN Inference/Training Processor For Embedded System
Enhanced parallel CFAR architecture with sharing resources using FPGA
Circularly Polarized E-Shaped Patch Antenna for AWS, FMS and MSS Applications
Information hiding mechanism based on QR code and information sharing algorithm
Hardware/Software Codesign for Energy Efficiency and Robustness: From Error-Tolerant Computing to Approximate Computing
Application of embedded fibre Bragg grating sensors for structural health monitoring of complex composite structures for marine applications
A 5nm Wide Voltage Range Ultra High Density SRAM Design for L2/L3 Cache Applications
Real time medical data monitoring and iodine 131 treatment of thyroid cancer nursing analysis based on embedded system
Modified embedded-atom method interatomic potentials for Mg–Al–Ca and Mg–Al–Zn ternary systems
Online Test Strategies and Optimizations for Reliable Reconfigurable Architectures
A sol-gel pretreatment combined strategy for constructing cobalt-embedded and nitrogen-doped carbon matrix with high-density active sites as bifunctional oxygen …
Architectures for Flexible Collaborative Systems
A model of architecture for estimating GPU processing performance and power
Switch based High Cardinality Node Detection
Research on electric vehicle charging scheduling algorithms based on a’fractional knapsack’
Polymer optical fiber-embedded force sensor system for assistive devices with dynamic compensation
A Compact FPGA-Based Accelerator for Curve-Based Cryptography in Wireless Sensor Networks
M2OS-Mc: An RTOS for Many-Core Processors
Truth Embedded in Form: Towards a New Literary Realism of Fields of Sense
Guest Editorial: Special Issue on Embedded Machine Learning
Investigating the Interaction between Energy Consumption, Quality of Service, Reliability, Security, and Maintainability of Computer Systems and Networks
Gain-Cell Embedded DRAM Under Cryogenic Operation–A First Study
A 3–7 GHz CMOS Power Amplifier Design for Ultra-Wide-Band Applications
Energy-aware automatic tuning on many-core platform via adaptive evolution
Real-time implementation of a parameterized Model Predictive Control for Attitude Control Systems of rigid-flexible satellite
… CARESSES Randomised Controlled Trial: Exploring the Health-Related Impact of Culturally Competent Artificial Intelligence Embedded Into Socially Assistive …
Side Channel Assessment Platforms and Tools for Ubiquitous Systems
Variability Analysis of On-Chip Interconnect System Using Prospective Neural Network
Impact of Multi-Metal Gate Stacks on the Performance of ß-Ga2O3 MOS Structure
Transformer-based Machine Translation for Low-resourced Languages embedded with Language Identification
Second-nearest-neighbor modified embedded-atom method interatomic potential for VM (M= Cu, Mo, Ti) binary systems
Incremental Few-shot Learning via Vector Quantization in Deep Embedded Space
Heart Rate Monitoring System
Nonlinear vibration suppression of composite laminated beam embedded with NiTiNOL-steel wire ropes
Mutation Analysis for Cyber-Physical Systems: Scalable Solutions and Results in the Space Domain
Based on machine learning scheme to develop a smart robot embedded with GMM-UBM
Qualitative and quantitative analysis of parallel-prefix adders
FPGA-Based Implementation of Artifact Suppression and Feature Extraction
Embedded System Hardware
[PS][PS] An Application for Extending the ARTES Project
A Study on the Efficiency of Deep Learning on Embedded Boards
Improved NSGA-II for the minimum constraint removal problem
DC-DC Converter for Powering Micro-system Load in Energy Harvesting Front-ends
Underwater Marine Life and Plastic Waste Detection Using Deep Learning and Raspberry Pi
Reliability Analysis and Mitigation of Near-Threshold Voltage (NTC) Caches
Graphitic carbon nitride embedded-Ag nanoparticle decorated-ZnWO 4 nanocomposite-based photoluminescence sensing of Hg 2+
DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing from Decentralised Data
Systematising troubleshooting of disputes in network
Novel Census Transform Hardware IP
Research on fuzzy clustering method for working status of mineral flotation process
The Tulipp Hardware Platform
Pickering emulsion-embedded hierarchical solid-liquid hydrogel spheres for static and flow photocatalysis
Dealing with Aging and Yield in Scaled Technologies
Manipulating Hubbard-type Coulomb blockade effect of metallic wires embedded in an insulator
Deterministic Digital Calibration of 1.5 bits/stage Pipelined ADCs by Direct Extraction of Calibration Coefficients
Effects of Pt and Au adsorption on the gas sensing performance of SnS2 monolayers: A DFT study
An Efficient Low Power MEMS-Based Microfluidic Device for the Segregation of Different Blood Components
Prospects of Two-dimensional Material-based Field-Effect Transistors for Analog/RF Applications
Low Power Extended Range Multi-Modulus Divider Using True-Single-Phase-Clock Logic
Towards complex dynamic fog network orchestration using embedded neural switch
Operationalisation of the Randomized Embedded Multifactorial Adaptive Platform for COVID-19 trials in a low and lower-middle income critical care learning …
Mining constant information for readable test data generation
Printed Structural Temperature Monitoring Embedded in Multi-Process Hybrid Additive Manufacturing
Design of a single phase switched boost inverter with important potential of conversion in variable conditions
Damage Detection in Multiple RC Structures Based on Embedded Ultrasonic Sensors and Wavelet Transform
Investigation of structural and optical properties of Pb1-xCoxS nanocrystals embedded in chalcogenide glass
Stochastic Model of a Sensor Node
SPD-Safe: Secure Administration of Railway Intelligent Transportation Systems
Ordered level spacing distribution in embedded random matrix ensembles
Exploiting Memory Resilience for Emerging Technologies: An Energy-Aware Resilience Exemplar for STT-RAM Memories
Crop pest recognition using attention-embedded lightweight network under field conditions
Selective Flip-Flop Optimization for Circuit Reliability
Data Acquisition Technique for Temperature Measurement Through DHT11 Sensor
Compact Dilithium Implementations on Cortex-M3 and Cortex-M4
A compact hardware implementation of CCA-secure key exchange mechanism CRYSTALS-KYBER on FPGA
The making of data commodities: data analytics as an embedded process
Compiler-Assisted Software Fault Tolerance for Bare Metal and RTOS Applications on Embedded Platforms
A Parallel Jacobi-Embedded Gauss-Seidel Method
Efficiency and safety assessment of suburban highway access management
Parameters extraction of single diode model for degraded photovoltaic modules
Ab initio molecular dynamics and materials design for embedded phase-change memory
LIS-Net: An end-to-end light interior search network for speech command recognition
Fault injection as an oscilloscope: fault correlation analysis
Abstract PR-01: Real-time, point-of-care pathology diagnosis via embedded deep learning
Monitor Circuits for Cross-Layer Resiliency
Design and development of embedded system of portable bicycle exerciser
Embedded Computer Vision System Applied to a Four-Legged Line Follower Robot
Implications of embedded artificial intelligence-machine learning on safety of machinery
In-Database Embedded Analytics A Major Qualifying Project report to be submitted to the faculty of
ISAMod: A Tool for Designing ASIPs by Comparing Different ISAs
Detection of mycobacteria in paraffin-embedded Ziehl–Neelsen-Stained tissues using digital pathology
Physical Constraint Embedded Neural Networks for inference and noise regulation
Self-Templated Hierarchically Porous Carbon Nanorods Embedded with Atomic Fe-N4 Active Sites as Efficient Oxygen Reduction Electrocatalysts in Zn-Air Batteries
IoT: Security Attacks and Countermeasures
Redundant code-based masking revisited
Security and Privacy Techniques in IoT Environment
Variational Method for Hydrogen Atom Embedded in Non-ideal Classical Plasmas
Training Neural Network for Machine Intelligence in Automatic Test Pattern Generator
Improving the quality of service of real-time database systems through a semantics-based scheduling strategy
Inter-Urban Analysis of Pedestrian and Drivers through a Vehicular Network Based on Hybrid Communications Embedded in a Portable Car System and Advanced …
Kannada Text-to-Speech System using MATLAB
Design of Electronic Instrumentation for Isotope Processing
Reliability tracking method of power system equipment based on Embedded Internet of things technology
An efficient algorithm for multiple-pursuer-multiple-evader pursuit/evasion game
Introduction to the Linux Environment
Simulation Analysis of Electro-Mechanical Property of Piezoelectric Fiber Composite with Embedded Interdigital Electrode
The design of scalar AES Instruction Set Extensions for RISC-V
Implementation of a Pet Care Robot Based on Webcam and Smartphone and its Power Management
TinyRadarNN: Combining spatial and temporal convolutional neural networks for embedded gesture recognition with short range radars
Visual management of sports training based on embedded wearable devices and machine vision
Forecasting Air Temperature on Edge Devices with Embedded AI
Development of a Portable, Reliable and Low-Cost Electrical Impedance Tomography System Using an Embedded System
Embedded Vision for Self-Driving on Forest Roads
A study on the dynamic behavior of a vertical tunnel shaft embedded in liquefiable ground during earthquakes
Graph-Embedded Convolutional Neural Network for Image-based EEG Emotion Recognition
Enhancing Air Quality for Embedded Hospital Germicidal Lamps. Sustainability 2021, 13, 2389
Fuzzy decision trees embedded with evolutionary fuzzy clustering for locating users using wireless signal strength in an indoor environment
Sustainable detection and capturing of cerium (III) using ligand embedded solid-state conjugate adsorbent
-block elemental-atom-embedded monolayers: Large magnetic moment, high-temperature ferromagnetism, and huge magnetic anisotropy energy
Lung carcinoma spheroids embedded in a microfluidic platform
Embedded solitons in second-harmonic-generating lattices
Design Considerations for Edge Neural Network Accelerators: An Industry Perspective
A study of embedded star clusters in reflection nebulae
A Systematic Review on an Embedded Web Server Architecture
Linear electromagnetic energy harvester system embedded on a vehicle suspension: From modeling to performance analysis
A review of regional distributed energy system planning and design
Up and Running with WebGL
A utility-aware multi-task scheduling method in cloud manufacturing using extended NSGA-II embedded with game theory
A methodology for detection and classification of power quality disturbances using a real-time operating system in the context of home energy management systems
A SnOx Quantum Dots Embedded Carbon Nanocage Network with Ultrahigh Li Storage Capacity
Fault Attacks on CCA-secure Lattice KEMs
Real-time instance segmentation of traffic videos for embedded devices
Design of embedded data analyzer based mitigation model for traffic congestion and its challenges
Fabrication and embedded sensors characterization of a micromachined water-propellant vaporizing liquid microthruster
The architecture of computer hardware, systems software, and networking: An information technology approach
ROS on ARM Processor Embedded with FPGA for Improvement of Robotic Computing
Design and Evaluation of a New Machine Learning Framework for IoT and Embedded Devices
Optimal parameter estimation of polymer electrolyte membrane fuel cells model with chaos embedded particle swarm optimization
Real-time anomaly detection in gas sensor streaming data
NTT Multiplication for NTT-unfriendly Rings
Early-Stage Neural Network Hardware Performance Analysis
Rationally embedded zinc oxide nanospheres serving as electron transport channels in bismuth vanadate/zinc oxide heterostructures for improved …
IOT: The Theoretical Fundamentals and Practical Applications
Real-time single image depth perception in the wild with handheld devices
Gellan-Based Composite System as a Potential Tool for the Treatment of Nervous Tissue Injuries: Cross-Linked Electrospun Nanofibers Embedded in a RC-33 …
A new weak curve fault attack on ECIES: embedded point validation is not enough during decryption.
Embedded Wireless Dissolved Oxygen Monitoring Based on Internet of Things Platform
SMART RIVER FLOATING GARBAGE CLEANING ROBOT USING IOT AND EMBEDDED SYSTEM
A Microvalve Module with High Chemical Inertness and Embedded Flow Heating for Microscale Gas Chromatography
Embedded fuzzy-based models in hydraulic jump prediction
Hardware-aware, context-scalable processing for embedded visual navigation
SHARKS: Smart Hacking Approaches for RisK Scanning in Internet-of-Things and Cyber-Physical Systems based on Machine Learning
Issues on Applying One-and Multi-Step Numerical Methods to Chaotic Oscillators for FPGA Implementation
On blockchain integration into mobile crowdsensing via smart embedded devices: A comprehensive survey

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Embedded Systems Project Topics With Abstracts and Base Papers 2024

Embark on a transformative journey into the world of embedded systems with our meticulously curated selection of M.Tech project topics for 2024, thoughtfully complemented by trending IEEE base papers. These projects encapsulate the forefront of innovation and challenges in embedded systems, offering an indispensable resource for M.Tech students seeking to delve into the dynamic landscape of intelligent and interconnected devices .Our comprehensive compilation covers a diverse range of Embedded Systems project topics, each intricately paired with an associated base paper and a succinct abstract. From IoT applications and real-time systems to edge computing and hardware-software co-design, these projects mirror the current trends in embedded systems development. Stay ahead of the curve by exploring projects that align with the latest IEEE standards and technological breakthroughs. Whether you’re a student, researcher, or industry professional, our collection serves as a gateway to the cutting edge of embedded systems advancements. The project titles are strategically chosen to incorporate keywords that resonate with the latest trends in embedded systems , ensuring relevance and alignment with the evolving technological landscape. Delve into the abstracts to quickly grasp the scope, methodologies, and potential impacts of each project.

M.Tech Projects Topics List In Embedded Systems

Research Topics in Embedded Systems for PhD

The amalgamation of software and hardware in a computer system is called an embedded system. The signal processors, microprocessors, and ...

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The amalgamation of software and hardware in a computer system is called an embedded system. The signal processors, microprocessors, and digital signal processors are functioning through the embedded systems. In addition, flexibility, scalability, energy, dependability, efficiency, and precision are some of the notable features of embedded systems. Let’s start this article with the significant research areas of embedded systems to derive the recent research topics in embedded systems for PhD.

Research Areas in Embedded Systems

Intelligent and solar-operated robot
Metal detector
Pc-based bomb detector
Heat controller
Rain detector
LCD thermometer
Voice dialer for phone
The speed limit of the vehicle
Driverless car
Gas leak detection
Train accident alert
Gesture control
Anti-sleep alarm
Auto door open
Fridge door alarm
Digital calendar
Biomedical monitoring system
Embedded-based auto lift
Fingerprint car ignition system

At this moment, let us take a look at the list of research algorithms in this field of embedded systems. In addition to that, the research scholars have to go through and finalize the research fields before getting into the selection of research topics in embedded systems for PhD because the algorithms also have to place the research topic in a short note.

Algorithms in Embedded Systems

The tasks in RMS are scheduled through the static priority which is determined using the duration. In addition, it guarantees time restraints capable of 70% CPU load
In this process LLF, the tasks are scheduled through the order of laxity and it is not functioning in the soft real-time applications, it has to compete with the applications that are in higher priority
It is denoted as the dynamic scheduling algorithm which is used in real-time operating systems. Along with that, it is accomplished to assign priority to the process which has the earliest deadline. The process of EDF is functioning over the tasks which are scheduled by the order of the deadline

For your quick reference, our technical experts in the embedded system have highlighted the list of substantial research ideas in the embedded system for your PhD topic selection. More than that, our research experts are ready to implement the scholar’s research ideas. So, discover the innovations with our better guidance.

Latest Interesting Research Ideas in Embedded Systems

Communication propagation and antenna
Embedded systems and secure applications
Cognitive science
Signal processing applications
Water level controller
PLC-based intruder information sharing
Land rover robot
Traffic signal auto stop
Ultrasonic and voice-based walking for blind
Multi-channel fire alarm
GPRS-based industrial monitoring
GSM-based ECG tele-alert system
Data acquisition system
Power failure indicator

Are you guys requiring the research topics in embedded systems for PhD with the discussion and to shape your research knowledge? Then you can approach our research experts at any time. The following is about the list of significant research topics that occurred in the contemporary research platform and it is used to select the project titles based on an embedded system.

Research Topics in Embedded Systems for PhD Scholars

Representation of embedded system with the Petri synthesis property preservation
Controlling the time nonlinear systems through the embedded systems
Analysis, application, and modeling
Nonvolatile data memory with a real-time embedded system
PCP water injection system design
Parallel heterogeneous system applications
Deep neural networks and voice recognition
Distinct stair recognition system and ultrasonic device frequency
LPWAN is used while monitoring the coastal waves
Power harvesting for smart sensor networks in monitoring water distribution system
Accelerometer-based gesture recognition for wheelchair direction control
Bedside patient monitoring with wireless sensor networks
4-GHz energy-efficient transmitter for wireless medical applications
Automatic docking system for recharging home surveillance robots
Hybrid RFID-GPS-based terminal system in vehicular communications
RF fingerprinting physical objects for anti-counterfeiting applications
Authenticated and access control system for the device using smart card technology
Hazardous gas detecting method applied in coal mine detection robot
Posture allocations and activities by a shoe-based wearable sensor
Development of an ES for secure wireless data communication
A microcontroller-based intelligent traffic controller system
Monitoring and controlling of requirements for cultivation

The following is about the list of research applications based on the embedded system research field it is beneficial for research scholars to find the finest PhD research work through the provided list and these are highlighted by our experienced research professionals in embedded systems.

Latest Research Topics in Embedded systems for phd scholars

Applications in Embedded Systems

Artificial intelligence and robotics
Telephones, satellite, and radio communications
Text interfaces
Military control bases
Firing of missiles
Patient monitoring
Heart treatments
Radiation therapy
Space station control
Spaceship launch and monitoring
Automobiles

We provide complete research assistance in the research field based on embedded systems for research scholars. On that note, the research scholars have to know about the components that are used in their selected research area. Thus, we have enlisted the components based on the embedded system for your quick reference to implement research topics in embedded systems for PhD.

Components in Embedded Systems

The power supply is considered the significant component to provide power to the embedded system circuit. In addition, the embedded system requires a 5 V supply that ranges from 1.8 to 3.3. V
32-bit processor
16-bit processor
8-bit processor
Several microcontrollers are utilized in the embedded system and the memory is the representation of the microcontroller itself. It includes two significant types as
RAM is denoted as the volatile type of memory and it is used to store the data for a temporary period in the memory while switching off the system, the data will be lost from the memory
It is denoted as the code memory and it is deployed to store the program when the system is switched on the embedded system fetch code from ROM memory
The input is used in the embedded system where it is needed to interact with the system. The processors are used in the embedded system based on input and output. In addition, the proper configuration is required for using the input and output ports. In the embedded system there are fixed input and output ports to connect the devices only with the specified ports and P0, P1, P2, and more are examples of input and output ports
The type of interface which is deployed to communicate with other types of embedded systems is called a communication port. When the small-scale application includes the embedded system and communication ports can be deployed in the form of a microcontroller and it includes the serial protocols used to send data from one system board to another system board
The timer and counter are utilized in the embedded system and the programming is done in such a way that delay can be generating the embedded system. The delay period can be decided through the functions of the crystal oscillator and system frequency
The application is used for embedded systems with the competition of hardware components. For instance, temperature sensor applications are requiring the temperature sensors to measure the temperature

Up to now, we have discussed some forceful research components that are used in an embedded system which every research scholar prerequisites to be aware of while selecting their research topics in an embedded system for PhD. Without any delay, let’s discuss research problems in the research field based on the embedded system in the following.

Research Challenges in Embedded Systems

Performance
DRM vs usability
Creating the required latent process
Moore’s law
Globalization
Future vs legacy
Emerging behavior
Heterogeneous vendors
Heterogeneity

Below, our research professionals have enlisted the research questions that are asked by the research scholars to develop their research projects in the embedded system along with the appropriate answers.

People Asked Questions

What are the top research fields in embedded systems.

Cyber security embedded system
Embedded IoT application
Embedded network design
Embedded applications
Embedded Linux system
Microcontroller firmware

What are the different types of embedded systems?

Mobile phones
Digital camera
Home security systems
ATM machine
Card swipe machine
MP3 players
Microwave ovens
Traffic control system
Military usage in the defense sector
Medical usage in the health sector

What is a new technology in embedded systems?

Cloud connectivity
Embedded security
Augmented reality and virtual reality
Artificial intelligence
Deep learning

What is the simulation tools used in embedded system?

What is the programming languages used in embedded system, what are the topics in embedded systems.

Wireless meter for consumer utility
An ultrasonic parking guidance system
Iris-based door opening and closing
Fault location in underground power networks
Embedded-based calibration of the proximity sensor
Accident prevention using eye blink
Earthquake analyzer and reporter
AC motor speed monitoring and control through telephone
Bus information alert for the blind using Zigbee

What are the real-time examples in embedded systems?

Medical Equipment
Electronic Calculators
Industrial machines
Laser Printer
Digital phones
Televisions
Washing Machine
Digital watches

To this end, the research scholars can trust us for your PhD work and we shape your innovative research thoughts with proper research implementation by using the required simulation tools, protocols, algorithms, etc. Our research experts have years of experience in this research platform and also from research topics in embedded systems for PhD to paper publication too. We are strong in all the research fields in embedded systems and we are being learned through the fundamentals till the growth and now. Finally, the research scholars will acquire the finest result when you join hands with us. As well as, we teach you an easy way to acquire the finest research knowledge to shine in your research career.

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Master theses from the Master Programme in Embedded Systems

Here you find lists of master theses written at the department for IT, by students from the Master Programme in Embedded Systems. Other programs: Master in computer science, older program , Bach. in computer science , Systems in technology and society , Msc in IT engineering , Master in computer science , Master in HCI , Master in computational science and the complete list .

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Chair of Integrated Systems
TUM School of Computation, Information and Technology
Technical University of Munich

Master Theses

Available topics.

Interested in an internship or a thesis? Often, new topics are in preparation for being advertised, which are not yet listed here. Sometimes there is also the possibility to define a topic matching your specific interests. Therefore, do not hesitate to contact our scientific staff, if you are interested in contributing to our work. If you have further questions concerning a thesis at the institute please contact Dr. Thomas Wild .

MA : Hardware-Aware Layer Fusion of Deep Neural Networks

Open thesis as PDF.

Hardware-Aware Layer Fusion of Deep Neural Networks

Description.

Dataflow and mapping of Convolutional Neural Networks (CNN) influences their compute and energy efficiency on edge accelerators. Layer fusion is a concept which enables the processing of multiple CNN layers without resorting to costly off-chip memory accesses. In order to optimally implement layer fusion, different combinations of mapping and scheduling parameters need to be explored. We, at the BMW group, offer you a challenging master thesis position that aims to optimize the fusion strategy of a given CNN workload for maximal data reuse and resource utilization.

Prerequisites

Strong knowledge in computer vision concepts, and convolutional neural networks.
Hands-on experience with Xilinx FPGAs, Verilog/VHDL/HLS.
Excellent programming skills in C, Python. Experience in Tensorflow 2, Git, Docker is a plus.
Highly motivated and eager to collaborate in a team.
Ability to speak and write in English fluently.

[email protected]

Supervisor:

Assigned topics, ma : hardware-accelerated linux kernel tracing, hardware-accelerated linux kernel tracing.

Tracing events with hardware components is one powerful tool to monitor, debug, and improve existing designs. Through this approach, detailed insights can be acquired, and peak performance can be achieved, while being a challenging task to be integrated with good performance. One of the major challenges of tracing is to collect as much information as possible with ideally no impact on the to-be-analyzed system. Herewith, it can be ensured that the gained insights are representative of an execution without any tracing enabled. In this work, a hardware tracing component should be leveraged to reduce the intrusiveness of existing software tracing mechanisms in the Linux kernel.

This should be integrated and tested on a hardware platform based on a Xilinx Zynq board. This features a heterogeneous ARM multicore setup directly integrated into the ASIC, combined with programmable logic in the FPGA part of the chip. In the FPGA a hardware accelerator is already implemented that should be traced with the new component.

To successfully complete this work, you should have:

experience with microcontroller programming,
basic knowledge about Git,
first experience with the Linux environment.

The student is expected to be highly motivated and independent.

MA : Multicore-Optimierung eines bildverarbeitenden Systems

Multicore-optimierung eines bildverarbeitenden systems.

Im industriellen Umfeld werden Informationen zunehmend in visuellen Codes (z.B. Strichcodes, QR-Codes) zur automatisierten Verarbeitung abgelegt. Steigende Durchsatzzahlen stellen immer höhere Anforderungen an die Geschwindigkeit der Datenverarbeitung. In dieser Arbeit soll anhand eines kostengünstigen kommerziell erhältlichen Multicore- Systems untersucht werden, inwieweit bisher durch Hardware realisierte Verarbeitungsgeschwindigkeiten durch Parallelisierung der Auswertungsschritte in CPU-Systemen erreicht, werden können. Insbesondere soll untersucht werden, ob spezialisierte Co-Prozessoren (z. B. Vector Processing Units (VPUs)) zur Beschleunigung beitragen können oder wie diese auf die Aufgabe hin optimiert gestaltet werden können (Application-Specific Instructionset Processor (ASIP)).

MA : A Deep Dive into C-States, Idle Governors and the Prospects of an eBPF Idle Governor

A deep dive into c-states, idle governors and the prospects of an ebpf idle governor.

Linux is one of the most utilized Operating Systems in Embedded Systems and Cloud Infrastructure worldwide. Sustainability will become more relevant in the future and saving power is a crucial aspect. This shows the increasing importance of efficient Linux Power Management.

The Power Management in Linux is implemented in several kernel subsystems correlating to hardware characteristics, like P-States (Frequency Scaling) and C-States (Sleep States). This thesis examines the Idle Power Management of Linux, and therefore focuses on C-States. C-States are per Core states and allow parts of the core to shut down individual features. Each processor implements C-States in different ways. Increasing C-State number, e.g. C6, translate to a deeper sleep with lower energy consumption and higher power-on reaction time.

The recently released eBPF functionality makes the kernel more programmable, bypassing the original monolithic characteristics. This mechanism can be divided into four components: the eBPF hooks in the kernel, the interfaces, the in-kernel eBPF infrastructure to execute eBPF bytecode and compile into native code and verify the code and finally the eBPF application itself, which can be written in a C like dialect and compiled into eBPF bytecode by LLVM and GCC.

This thesis aims to analyze and compare the idle governors in the current Kernel in specific situations. It also should provide insight in the C-State usage depending on the architecture. The data is acquired using specific Tracepoints within the Kernel, which can be recorded and parsed with the Kernel Tool perf. Furthermore, we explore the feasibility of a custom eBPF powered idle governor.

MA : Design and Implementation of a Memory Prefetching Mechanism on an FPGA Prototype

Design and implementation of a memory prefetching mechanism on an fpga prototype.

Their main advantages are an easy design with only 1 Transistor per Bit and a high memory density make DRAM omnipresend in most computer architectures. However, DRAM accesses are rather slow and require a dedicated DRAM controller that coordinates the read and write accesses to the DRAM as well as the refresh cycles. In order to reduce the DRAM access latency, memory prefetching is a common technique to access data prior to their actual usage. However, this requires sophisticated prediction algorithms in order to prefetch the right data at the right time. The Goal of this thesis is to design and implement a DAM preloading mechanism in an existing FPGA based prototype platform and to evaluate the design appropriately. Towards this goal, you'll complete the following tasks: 1. Understanding the existing Memory Access mechanism 2. VHDL implementation of the preloading functionalities 3. Write and execute small baremetal test programs 4. Analyse and discuss the performance results

Good Knowledge about MPSoCs
Good VHDL skills
Good C programming skills
High motivation
Self-responsible workstyle

Oliver Lenke

[email protected]

MA : SmartNIC Enhancements for Network Node Resilience

Smartnic enhancements for network node resilience.

The Chair of Integrated Systems participates in the DFG Priority Program “Resilient Connected Worlds” by the German Research Foundation (SPP 2378). Our goal is to investigate which resilience functions, that conventionally are provisioned by the central compute resources of Internet Networking or Compute Nodes, can meaningfully be migrated onto the Network Interface Card (NIC). By inspecting packet streams at full line rate (10 – 40 Gbps) a set of resilience functions, such as access shields against a known set of traffic flows or redundant flow processing for a selected and configured number of flows, shall be offloaded from centralized compute resources and offered in a more performant and energy-efficient manner. Flows are identified by their so-called 5-tuple consisting of source-/destination IP addresses and transport protocol ports as well as the protocol field of the IP packet header. During the Bachelor/Master Thesis, you will develop VHDL code for realizing one or more of the SmartNIC Resilience building blocks: 5 tuple address matching against a preconfigured set of addresses, perform the packet duplication for delivery to different processor cores or threads, investigate methods to flexibly perform the address match on the entire or a variable subsection of the 5 tuple array.

VHDL coding, synthesis and FPGA prototyping
Braodband communication or Internet Networking Technologies, in particular OSI Layer packet header formats
Digital circuit design

Marco Liess Room N2139 Tel. 089 289 23873 [email protected]

MA : Parsimonious Semantic Segmentation Training Using Active Learning and Synthetic Data

Parsimonious semantic segmentation training using active learning and synthetic data.

The goal of this thesis is to implement an augmentation pipeline for both runtime accuracy improvement and training time generalization. At training time the augmented examples add diversity to the dataset, while at runtime the augmentation injects more information in addition to the RGB color channels, to help the CNN detect semantic segmentation features. The thesis will also explore different loss formulas and loss learning to make training semantic segmentation easier with fewer labeled examples. Finally, the CNN will be pruned and quantized for faster execution, while the rest of the processing (pre, post) pipeline will be accelerated on GPU.

To successfully complete this project, you should have the following skills and experiences:

Good programming skills in Python and Tensorflow
Good knowledge of neural network training theory
Experience with convolutional neural networks for semantic segementation

The student is expected to be highly motivated.

Nael Fasfous Department of Electrical and Computer Engineering Chair of Integrated Systems

Phone: +49.89.289.23858 Building: N1 (Theresienstr. 90) Room: N2116 Email: [email protected]

MA : Neural Style Transfer for Synthetic Data

Neural style transfer for synthetic data.

Neural networks have become the state-of-the-art in solving a variety of computer-vision problems, often outperforming classical image processing algorithms by a large margin. These applications range from autonomous vehicles to complex control of robots. However, training neural networks presents some difficulties. First and foremost is the cost of human effort to label and collect suitable training data (number and critical situations) in production environments for training purposes. Synthetic training data is one potential solution to this challenge.

In the context of this work, a neural network for the control of an automated production line should be trained using synthetic data. For this purpose the following milestones planned:

Developement of a 3D-model for the generation of training data.
Automatic synthesis of images and ground truth data to train the image processing algorithm.
Adaptation of the synthetic training data to the real world (style transfer)
Outperforming neural networks classically trained on limited amount of real data

Alexander Frickenstein Email: [email protected]

MA : Anomaly Detection and Active Learning for Semantic Segmentation Tasks

Anomaly detection and active learning for semantic segmentation tasks.

Clean, labeled datasets are an invaluable asset to research and industry for training and deploying machine learning algorithms such as convolutional neural networks (CNN). Procuring such datasets involves data collection, sorting and labeling, all of which are typically done by humans. This expensive process is time consuming, costly and does not scale well, even when outsourced. The field of anomaly detection and active learning aims to tackle these challenges. In active learning, a CNN can be trained on a small set of labeled data. Once deployed in a real-world scenario, an uncertainty or loss predictor can be implemented alongside the algorithm to predict which data would result in high loss for the model. These non-trivial examples can be collected actively during deployment and forwarded to humans or more complex algorithms to observe, label and retrain the deployed CNN on. In anomaly detection, a network can predict which samples represent outliers or interesting anomalies with respect to the rest of the dataset. This further helps humans clean and sort such examples accordingly.

The goal of this thesis is to implement an anomaly detector and an uncertainity head to a CNN-based semantic segmentation application. The implementation will be tested on a real-world industrial AI application.

MA : Learning to Prune and Quantize Transformers

Learning to prune and quantize transformers.

Advances in the deep learning architectures for computer vision applications have lead to new neural architectures such as vision transformers. These differentiate themselves from typical convolutional neural network-based implementations by decoupling the process of feature aggregation and transformation. Excellent performance is achieved through self-attention and self-supervision.

In this master thesis, visual transformers will be implemented in the first step. Following verification of state-of-the-art results, the transformers will be compressed through quantization and pruning to minimize their computational complexity on the inference hardware.

Good knowledge of neural networks, basic knowledge of transformers

MA : Sparse Lookup Tables with dynamic precision adaptation for image processing on FPGA

Sparse lookup tables with dynamic precision adaptation for image processing on fpga.

In image processing, non-linear transfer functions, such as sigmoid- or logarithm-shaped functions, are being used for mapping the input into different domains. For dedicated FPGA implementation of general image processing pipelines, these transfer functions are usually implemented by LUTs (Lookup Tables). Although the LUT-based method is more concise than some approximate direct implementation, it consumes a lot of resources. To save FPGA resources, sparse LUTs can be used, but it is to be noticed that the matching accuracy is then approximated to a certain acceptable range.

To further reduce the resource consumption, while maintaining or even improving the output accuracy, we propose a dynamic loading mechanism. In order to make full use of the resources on the chip, instead of placing one sparse LUT on chip, two function-wise complemented memory blocks shall be implemented in the data path of the processing pipeline. One of the memory blocks shall be filled only with the data points that fit the local range of current input data stream. Another one works as a general ultra-sparse LUT to map the input data into the inaccurate global range. In summary, a permanent memory block of very sparse/inaccurate data points should be kept on FPGA, which is then complemented by a memory block of accurate data points which are dynamically swapped in and out from an off-chip memory (DRAM). Based on this proposal, we need to investigate a dynamic loading mechanism for that accurate memory block, such that the input will fall into the local range with rational high probability.

In this work, a prototype of a sparse LUT with a dynamic precision adaptation mechanism should be developed on FPGA. In this thesis, several questions should be answered:

• How does the architecture of the implementation look like?

• What memory configuration should be used?

• How to determine when to load new data for the accurate memory block?

• What is the trade-off between accuracy and resource consumption?

MA : Runtime Reconfigurable Winograd-based FPGA Accelerator for CNN Inference

Runtime reconfigurable winograd-based fpga accelerator for cnn inference.

Convolutional neural networks have proven their success in extracting features from images and producing predictions for different tasks such as classification, segmentation and object detection. However, the superior performance of modern deep neural networks can be mostly backtracked to high model complexity and extensive hardware requirements. In this research internship, the complexity of convolution is reduced by quantization and Winograd minimal filtering algorithms. The prediction quality is regulated using dynamic reconfigurable Winograd acceleration.

Good programming skills in C/C++
Good knowledge of neural networks, particularly convolutional neural networks
VHDL/Verilog or OpenCL would be encouraged.

The student is expected to be highly motivated and independent. By completing this project, you will be able to:

Understand the impact of quantization, Winograd convolution and task specific accuracy.
Implementation of run-time reconfigurable Winograd Convolution on FPGA using OpenCL.
Evaluate trade-offs between flexibility, prediction accuracy and resource consumption

Manoj Vemparala Autonomous Driving BMW AG

Email: [email protected]

Nael Fasfous

Department of Electrical and Computer Engineering Chair of Integrated Systems

Phone: +49.89.289.23858 Building: N1 (Theresienstr. 90) Room: N2116 Email: [email protected]

embedded systems Recently Published Documents

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A Modular End-to-End Framework for Secure Firmware Updates on Embedded Systems

Firmware refers to device read-only resident code which includes microcode and macro-instruction-level routines. For Internet-of-Things (IoT) devices without an operating system, firmware includes all the necessary instructions on how such embedded systems operate and communicate. Thus, firmware updates are essential parts of device functionality. They provide the ability to patch vulnerabilities, address operational issues, and improve device reliability and performance during the lifetime of the system. This process, however, is often exploited by attackers in order to inject malicious firmware code into the embedded device. In this article, we present a framework for secure firmware updates on embedded systems. This approach is based on hardware primitives and cryptographic modules, and it can be deployed in environments where communication channels might be insecure. The implementation of the framework is flexible, as it can be adapted in regards to the IoT device’s available hardware resources and constraints. Our security analysis shows that our framework is resilient to a variety of attack vectors. The experimental setup demonstrates the feasibility of the approach. By implementing a variety of test cases on FPGA, we demonstrate the adaptability and performance of the framework. Experiments indicate that the update procedure for a 1183-kB firmware image could be achieved, in a secure manner, under 1.73 seconds.

Computer development based embedded systems in precision agriculture: tools and application

Low-power on-chip implementation of enhanced svm algorithm for sensors fusion-based activity classification in lightweighted edge devices.

Smart homes assist users by providing convenient services from activity classification with the help of machine learning (ML) technology. However, most of the conventional high-performance ML algorithms require relatively high power consumption and memory usage due to their complex structure. Moreover, previous studies on lightweight ML/DL models for human activity classification still require relatively high resources for extremely resource-limited embedded systems; thus, they are inapplicable for smart homes’ embedded system environments. Therefore, in this study, we propose a low-power, memory-efficient, high-speed ML algorithm for smart home activity data classification suitable for an extremely resource-constrained environment. We propose a method for comprehending smart home activity data as image data, hence using the MNIST dataset as a substitute for real-world activity data. The proposed ML algorithm consists of three parts: data preprocessing, training, and classification. In data preprocessing, training data of the same label are grouped into further detailed clusters. The training process generates hyperplanes by accumulating and thresholding from each cluster of preprocessed data. Finally, the classification process classifies input data by calculating the similarity between the input data and each hyperplane using the bitwise-operation-based error function. We verified our algorithm on `Raspberry Pi 3’ and `STM32 Discovery board’ embedded systems by loading trained hyperplanes and performing classification on 1000 training data. Compared to a linear support vector machine implemented from Tensorflow Lite, the proposed algorithm improved memory usage to 15.41%, power consumption to 41.7%, performance up to 50.4%, and power per accuracy to 39.2%. Moreover, compared to a convolutional neural network model, the proposed model improved memory usage to 15.41%, power consumption to 61.17%, performance to 57.6%, and power per accuracy to 55.4%.

Getting Started with Secure Embedded Systems

Design principles for embedded systems, cyense: cyclic energy-aware scheduling for energy-harvested embedded systems, embedded systems software development, esqumo an embedded software quality model.

Embedded systems are increasingly used in our daily life due to their importance. They are computer platforms consisting of hardware and software. They run specific tasks to realize functional and non functional requirements. Several specific quality attributes were identified as relevant to the embedded system domain. However, the existent general quality models do not address clearly these specific quality attributes. Hence, the proposition of quality models which address the relevant quality attributes of embedded systems needs more attention and investigation. The major goal of this paper is to propose a new quality model (called ESQuMo for Embedded Software Quality Model) which provides a better understanding of quality in the context of embedded software. Besides, it focuses the light on the relevant attributes of the embedded software and addresses clearly the importance of these attributes. In fact, ESQuMo is based on the well-established ISO/IEC 25010 standard quality model.

Embedded Systems and Architectures

Embedded systems and application areas in engineering, export citation format, share document.

University of Twente Student Theses

Programme: embedded systems msc (60331).

Nadar, Aditya (2024) Perspective Interactions : Detecting Multimodal Social interactions from an Egocentric View.

Reddy, Suhaas Veera Raghavan (2024) Joint Contribution-Based Client Selection and Resource Allocation leveraging Power Domain NOMA Network.

Weide, Luuk van der (2024) Near-Miss Detection on Traffic Intersections with a Distributed Overlapping Multi-Camera System.

Wijhe, Victor van (2024) Signal Processing with AMD Adaptive Compute Acceleration Platform (ACAP) for Applications in Radio Astronomy.

Aguilar Boj, E. (2023) Electrochemical impedance spectroscopy of lithium-ion batteries : a data-driven modelling approach using distribution of relaxation times.

Belle Lakshminarayan, Suhas (2023) Fuzzing : A Comparison of Fuzzing Tools.

Berg, C. van den (2023) Design of a No Reference Random Bin Picking System For Metal Plate Parts.

Burgt, A.P. van der (2023) AI in the Wild : Robust evaluation and optimized fine-tuning of machine learning algorithms deployed on the edge.

Böhmer, Kevin (2023) Radiation resilience evaluation of a Flash-based FPGA with a soft RISC-V Core.

Dadhich, Shrasti (2023) Increasing the accuracy of rodent detection and estimation of the population with emerging sensor technology.

Doornkamp, C.J. (2023) Dependable Probabilistic Energy Forecasting of Solar Energy for Energy Management Systems.

Fikse, J. (2023) Bluetooth Direction Finding using a Uniform Rectangular Array.

Fopma, Remmelt (2023) Study the outdoor performance of an open-hardware/source race-level quadrotor.

Gangireddy, Rajesh (2023) Knowing the Unknown : Open-World Recognition for Biodiversity Datasets.

Goswami, H. (2023) A framework for detecting and preventing DoS attacks in automotive ethernet switches.

Hagens, Florian (2023) Efficient Task Dispatching for Real-Time Systems: A Case Study in FreeRTOS.

Hofsté, G. te (2023) Evaluation of On-line Reconfiguration Techniques for a Distributed Avionic Middleware.

Huffelen, W.G.H. van (2023) Observability of off-the-shelf microarchitectures based on the RISC-V Instruction Set Architecture.

Linden, M.M. van der (2023) Federated Learning for Indoor Human Activity Recognition: Adapting to Changing Realistic Environments.

Meijer, J.J.W. (2023) Towards Future Proof Cryptographic Implementations: Side-Channel Analysis On Post-Quantum Key Encapsulation Mechanism CRYSTALS - Kyber.

Middelkoop, Daan (2023) Mapping Hardware Descriptions to Bittide Synchronized Multiprocessors for Instruction Level Parallelism.

Ravichandran, R. (2023) Improving accuracy of vehicle tracking by fusing IMU and GPS.

Ridder, Frank (2023) Adaptive Random Forest on FPGA.

Salce, Miss Yasmin (2023) Applying a Machine Learning Model to Estimate the Current State of Charge of Energy Storage Devices.

Slebos, Stijn (2023) Experimental study of a novel RF sensing application for measuring soluble sugar and electrical conductivity in the tomato plant stem.

Surya, Siddharth (2023) Detection of Japanese Knotweed Beside the Road using Deep Learning.

Uchoa Bezerra, H. (2023) Applying nucleotide sequence alignment techniques to side channel analysis.

Velmurugan, Pranesh (2023) Species Distribution Modelling : A Multimodal Learning Approach.

Veltman, Mike (2023) Comparative Study of Fault Detection and Diagnosis for Low-Speed Ball Bearings.

Wesselink, Bram (2023) Reducing resource utilization when simulating hardware in CLaSH.

Wijnja, S.N. (2023) Optimizing Data Movement for Accelerator Cards Using a Software Cache.

Willemsen, L.G. (2023) A Simple Homomorphic Obfuscation Scheme over Automorphisms.

Annink, E.B. (2022) Preventing soft-errors and hardware trojans in embedded RISC-V cores.

Balaji, R. (2022) Side channel pattern matching using neural networks on FPGA.

Benjamin Leonard, C. (2022) Wearable device for interactive and collaborative sound making for autistic people.

Boe, M. (2022) Realtime and Onboard fault diagnosis of UAV motors using RNN prediction model.

Chawane, Shruti (2022) Image based bee health classification.

Corts, R. (2022) Accelerating selective sweep detection software with the GPU architecture.

Dadhich, S. (2022) Increasing the accuracy of rodent detection and estimation of the population with sensor fusion.

Groffen, M.M.L. (2022) Exploring identity matching for low quality images with the help of a pipeline for synthetic face generation.

Hijlkema, Frank (2022) Direction-of-Arrival Estimation Using A Machine Learning Framework.

Kellaway, M.C. (2022) Accelerating the SCION IP Gateway using programmable data planes.

Loo, R. van (2022) Investigating Approximate FPGA multiplication for increased power-efficiency.

Murugeshan, J. (2022) Acoustic monitoring of airborne insects in outdoor environments.

Nair, M.G.N (2022) Item availability restricted.

Nijhuis, W.H. (2022) An audio based feature detector for shavers using Artificial Intelligence.

Nijkamp, Bas (2022) A High Throughput Sorting Accelerator using an Intel PAC FPGA.

Pennestri, Pietro. (2022) An FPGA based sensor fusion algorithm for IMU data processing.

Prasad, Pralad (2022) Automatic Clinical Deterioration Monitoring using Machine Learning Techniques Post Surgery.

Ramamoorthy, Adhithya (2022) Development of a UWB-IMU Body Motion Sensor.

Sankaran, A. (2022) Recurrent spiking neural networks in FPGA for signal processing applications.

Staal, P.J. (2022) On Productive, Low-Level Languages for Real-World FPGAs.

Thoonen, Maarten (2022) Using activity recognition to improve heart rate monitoring accuracy.

Tian, X. (2022) Reconstruction-based Anomaly Detection with Machine Learning for High Throughput Scanning Electron Microscope Defect Inspection.

Albers, J. (2021) Item availability restricted.

Ampudia, Ricardo (2021) Visible Light Positioning for Unmanned Aerial Vehicles.

Balciunas, J.K. (2021) Real-Time Interrupt-driven Concurrency (RTIC) for Modern Application Processors.

Baumgartner, Wolfgang Andreas (2021) Efficient Video Pipelines for Drone Applications.

Bollen, L.M. (2021) Hardware acceleration of sweep detection using Clash : Computer Architecture for Embedded Systems.

Chandra Mohan, Tejas (2021) Blind Image Quality Assessment of Smartphone-captured Images in the Wild.

Dijkshoorn, P.C. (2021) Low power ASIC design of a DDPSK demodulator.

Evers, M. (2021) The design of a prototype handheld 3D surface reconstruction setup for monitoring skin diseases.

Francis, Carolynn (2021) Interactive system for rhythmic synchronisation.

Govindaraj, Visshnu (2021) Forward collision warning system with visual distraction detection in bikes.

Griët, D.D. (2021) Automatically map an algorithmic description to reconfigurable hardware using the Decoupled Access-Execute architecture.

Haar, J. ter (2021) Design Reconstruction for Partial Reconfigurable FPGA Systems.

Heinsius, L.R. (2021) Real-Time YOLOv4 FPGA Design with Catapult High-Level Synthesis.

Hillerström, M.A.M. (2021) Towards Implicit Authentication in Smart Logistics: A Random Number Generator for Sensor PUFs in Resource Constrained IoT Devices.

Indrawijaya, K.R. (2021) Covariance Model Based Keypoint Detector Development.

Kalaiselvan, Kaushik (2021) Early Warning System for Safe Lateral Maneuver of Bicycles.

Keekstra, D.L. (2021) Tracking and segmentation, a tool for assessment of human engineered heart tissue.

Klute, L. R. W. (2021) Space-time Trade-off in Clash: Improving Smart Machines.

Knoben, P.A.H. (2021) Software caching for tree-based algorithms on accelerator cards.

Krishnamurthy, Ramesh (2021) ADA Software Model Checking.

Meijer, A. (2021) Real-time robot software framework on Raspberry PI using Xenomai and ROS2.

Postmes, J.M. (2021) Design of an efficient path planning and target assignment system for robotic swarms in agricultural applications.

Rali, S.K. (2021) Wearable coach for symmetric walking.

Ranjit Jacob, Sonu (2021) Lameness Detection from Top View : State-of-the-art Analysis of Lameness Detection.

Ravi Prame, Akash (2021) Hybrid Learning for Leakage Detection in Sealed Detergent Containers using IR-Thermography.

Rikkerink, K.B.W. (2021) Enabling Perspective Multiplication for Multi-Perspective Enrollment with University of Twente Finger Vein Scanner.

Schellekens, M.C.C. (2021) A Low-Budget, End-To-End Warning System for Bicycles using Monocular Vision and Vibrating Handlebars.

Sinha, Shreya (2021) Completely Automated CNN Architecture Design Based on VGG Blocks for Fingerprinting Localisation.

Smit, Kevin (2021) A high resolution grip strength measuring system for rehabilitation of hand conditions.

Sosale Pavamana, Prasanna (2021) Improving Process Traceability Using Deep-Learning Based Unsupervised Feature Extraction.

Souilljee, M.L. (2021) Locating Selective Sweeps with Accelerated Convolutional Neural Networks.

Spil, Gino van (2021) Device optimization using machine learning with hybrid heat pumps.

Strijker, H.W. (2021) Ethernet implementation in Clash.

Tamarin, E. (2021) Item availability restricted.

Uytdewilligen, M. (2021) Item availability restricted.

Vashistha, G. (2021) Robot assisted needle positioning system for liver biopsy.

Wolters, S.H.G. (2021) Accelerated Implementation of 3D Visual EKF SLAM For Handheld Perfusion Imaging.

Aniraj, Ananthu (2020) Item availability restricted.

Bos, L.C. (2020) Formal analysis and verification of interactions in the O2N middleware framework.

Bremmer, D.J. (2020) Mapping dataflow over multiple FPGAs in Clash.

Brinke, N.J. ten (2020) Direct-sequence spread spectrum in backscatter wireless sensor networks.

Diphoorn, W. (2020) A Smartphone Application for the Creation of Legal Document Photographs.

Grimm, Sander (2020) Design of a 3D imaging system for psoriasis assesment.

Huisman, Sander (2020) ClaSH-based Framework for Hardware Generation of Optimised Real-Time SDRAM Interfaces Using Static Memory Access Patterns.

Kesteloo, T.V. (2020) Autonomous navigation for the pipeline inspection robot "PIRATE".

Koomen, R.P.J. (2020) Evaluation of rapid development of embedded control software for cyber-physical systems with feature-based development cycles.

Oedzes, J.M. (2020) ASIP design and algorithm implementation for beamforming in an antenna array.

Ouyang, Cijun (2020) Robot Navigation in Dynamic Environment Based on Reinforcement Learning.

Padubidri, C.P. (2020) Sea lion Counting from Aerial Images with Deep Learning : A density Map Approach.

Perera, Navoda (2020) An API for intelligent deployment of numerical calculations.

Rawat, K. (2020) Human activity recognition based on energy efficient schemes.

Redonet Klip, T.H. (2020) Monitoring crowd dynamics by passively sniffing cellular traffic.

Robson, Francis (2020) Using Temperature and Humidity Sensors to Propose a New Form of Flat Roof Leakage Detection.

Smit, Vincent J. (2020) Self-healing approximate multipliers in MAC.

Stuurman, A. and Jongh, Dr. A. de (2020) Improving frequency estimation of fingerprint minutia configurations using automated pre-selection.

Tersteeg, Stefan (2020) Autonomous driving the pirate robot.

Westerveld, J.P. van (2020) FPGA partial reconfiguration and automatic variant generation as a side-channel attack countermeasure with functional HDL Clash.

Yeleshetty, Deepak (2020) Item availability restricted.

Zandberg, Koen (2020) Dataflow-Based Model-Driven Engineering of Control Systems.

Abdul Cader Hasanain, Mohamed Asif Hassan (2019) Item availability restricted.

Berg, R.T. Van den (2019) Designing a small and low-energy wildlife tag for parakeets within an urban environment capable of tracking and online activity recognition.

Beuker, W. (2019) Multi-rate discrete fourier transform characteristics : results of models, simulations, and measurements.

Bruijn, M.N. (2019) Increasing deterministic behavior of mobile robots by adding a safety layer.

Coenen, M.H. (2019) Increasing availability of the AEpu by improving the update process.

Delft, M. van (2019) Towards feature-based underground void detection with ground penetrating radar from within sewers using image processing.

Gerth, Jasper (2019) Development of a system for real time localization of a team of athletes using Ultra Wide band : design choices and considerations for mesh network localization.

Heijdens, R.H.M. (2019) Design of a mastitis indicator sensor.

Hogenkamp, Tom (2019) Framework for Fine-Grained Partial Reconfiguration on FPGAs.

Jansen, Bas (2019) Automated Testing of Models of Cyber-Physical Systems.

Jong, R.J. de (2019) Range characterization of backscatter Wireless Sensor Networks.

Krapukhin, Alexander (2019) Approximate Least Squares Accelerator.

Kulkarni, Vishwajit Vijay (2019) Embedded wearable device for monitoring diabetic foot ulcer parameters.

Lebbing, Peter (2019) Modelling and Realizing the Tunnelling Ball Device in UniTi and CλaSH.

Pohekar, Ashwini (2019) ASIP design on behalf of hybrid beamforming in MIMO communication system.

Raalte, E. van (2019) Automating system generation in Clash.

Radl, P.D. (2019) 3D reconstruction improvement by path planning towards physical interaction with a UAV.

Ramesh, Darshan (2019) Item availability restricted.

Rayo Torres Rodriguez, H. (2019) A lightweight hardware architecture for intermittent computing.

Reddy, Navin Ramesh (2019) Driving Behaviour Classification : An Eco-driving Approach.

Schipper, M.A. (2019) Decomposed reachability analysis for discrete linear systems.

Veenstra, G.W. (2019) Generating high frame rate MR images using surrogate signals.

Visser, L.E. (2019) Navigation for PDT in the paranasal sinuses using virtual views.

Wijlens, B. (2019) Building a framework in Clash to create deterministic sensor and actuator interfaces for FPGAs.

Yadav, Shubham (2019) An Asynchronous Approach for Designing Robust Low Power Circuits.

Zulkarnaen, Z. (2019) Separation of Interaction Wrench and Wind Disturbances from Wrench Observer in Fully-Actuated UAVs.

Bagave, Prachi (2018) Unobtrusive sensing using WiFi signals.

Chandramohan, Aashik (2018) Machine learning for cooperative automated driving.

Daulay, B.Eng O.F.P.G (2018) Investigating Planar Balun Structures with inherent impedance transformation and power combining properties.

Fatseas, K. (2018) Embedded neural network design on the ZYBO FPGA for vision based object localization.

Geerlings, S.A. (2018) Analysis and Design of a Dependability Manager for Self-Aware System-on-Chips.

Hoekstra, G.I.S. (2018) Towards a software architecture model for the automation of the PIRATE robot.

Hoekstra, K. (2018) On the realization of a smart grid demo-site at Coteq in Almelo.

Hofstra, Silke (2018) Automated analysis and simulation of control systems using dataflow.

Kers, Richard Jacob (2018) Low Energy Multi-Hop Mesh Network for Nomadic Localisation Sensors: On the Design, Development and Deployment.

Kers, T (2018) Household occupancy detection for burglary purposes : Risk assessment and effectivity analysis of an unobtrusive, easy-to-implement countermeasure against Wi-Fi tracking.

Khattab, A. A. M. (2018) Towards an interactive drone : a Bayesian optimization approach.

Klein Nijenhuis, T.A.J. (2018) Discovery and Quantification of Open DNS Resolvers on IPv6.

Meciani, Giovanni (2018) Implementation of a power-efficient DFT based demodulator for BFSK.

Roelofs, R.H. (2018) Using the Object Management Group Data Distribution Service to reliably teleoperate robotic systems.

Shokry, Kirelloss (2018) Generating high frame rate MRI images using a surrogate signal A Supervised Learning Approach.

Wardhana, Girindra (2018) Automatic Segmentation and 3D Reconstruction of Liver and Tumor.

Beekhof, H.M. (2017) High speed FPGA based scalable parallel demodulator design.

Brakels, M. (2017) Forward error correction and failure rates on Aurora high-speed links.

Brink, A.B. van den (2017) Evaluating Performance and Energy Efficiency of the Hybrid Memory Cube Technology.

Dzulqarnain, A.R. (2017) Distributed Processing for Operational Modal Analysis of Bridge Infrastructures Using Wireless Sensor Networks.

Fouda, Kareem M.I.A. (2017) Payload based signature generation for DDoS attacks.

Gottimukkala, Anirudh (2017) Implementation of a digital Class - D amplifier controller in CλaSH.

Kuipers, F.P. (2017) FPGA design support using CλaSH and LUNA.

Meteer, O. (2017) Real-Time rasterization on the Starburst MPSoC.

Mortezavi Matin, Kiavash (2017) Exploiting FPGA on RaMstix for vision applications.

QIN, L. (2017) Operator control hierarchy for multiple robot systems.

Terrivel, M (2017) Computationally Efficient Vision-based Robot Control.

Verkleij, Jelmer (2017) Behavioural analysis of program intent using data origins, influence and context.

Vree, J.H. de (2017) Design of an Energy Efficient 12-bit 100MS/s SAR ADC in 22nm FD-SOI.

Wang, Haitao (2017) Redesign of the E-Cone: A tool for treatment of hand disease.

Wang, Zhiyuan (2017) Slow wireless communication testbed based on software-defined radio.

Wentink, D.J.M. (2017) Signal Recovery using CλaSH.

Appel, R.N. and Folmer, H.H (2016) Analysis, optimization, and design of a SLAM solution for an implementation on reconfigurable hardware (FPGA) using CλaSH.

Bokhove, T. (2016) Improving the model management workflow.

Etheredge, C.E. (2016) GoSlow: Design and Implementation of a Scalable Camera Array for High-Speed Imaging.

Folmer, H.H. and Appel, R.N. (2016) Analysis, optimization, and design of a SLAM solution for an implementation on reconfigurable hardware(FPGA) using CλaSH.

Hakkenberg, Chiel (2016) Experimental evaluation of LoRa(WAN) in indoor and outdoor environments.

Kok, K.J. (2016) TERRA support for architecture modeling.

Nutma, J. (2016) More comprehensive demand side management by the integration of the powermatcher and triana.

Pakhira, A. (2016) A Fault Injection Framework for Reliability Evaluation of Networks on Chip Designed for Space Applications.

Suleymanov, S. (2016) Design and Implementation of an FMCW Radar Signal Processing Module for Automotive Applications.

Trillhose, Frank T. (2016) Controlling the production cell using TERRA-LUNA.

Veer, D. van der (2016) Design of a GMSK Receiver Prototype on a Heterogeneous Real-time Multiprocessor Platform.

Venema, M. (2016) DM3730 Camera interfaces on Gumstix.

Verheij, J.G.J. (2016) Co-simulation between CλaSH and traditional HDLs.

Vijver, B. van de (2016) A Human Robot Interaction Toolkit with Heterogeneous Multilevel Multimodal Mixing.

Vossen, J.J. van (2016) Offloading Haskell functions onto an FPGA.

Vries, J.J. de (2016) A Tick Based Fixed Priority Scheduler Suitable for Dataflow Analysis of Task Graphs.

Werff, W.M. van der (2016) Connecting ROS to the LUNA embedded real-time framework.

Wolf, T. (2016) Design of an Air Factor Sensor based on Light Emission.

DAM, M.R. (2015) Auditory processing using CλaSH.

FU, Q. (2015) Implementing a real-time control algorithm of Triana on SASensor Open Platform.

Hakim, V.S. El (2015) Implementation and Analysis of Real-time Object Tracking on the Starburst MPSoC.

Harmsen, Ruud (2015) Specifying the WaveCore in CλaSH.

Heukels, F.R (2015) Simultaneous Localization and Mapping (SLAM) : towards an autonomous search and rescue aiding drone.

Huizenga, G.R. (2015) A Front-end Application for Markov Random Field-based Texture Image Segmentation.

Kamminga, J.W. (2015) Cooperative Localisation on Android Devices by Utilising only Environmental Sound.

Raa, I. te (2015) Recursive functional hardware descriptions using CλaSH.

Starink, O.A.W. (2015) State-Save Overhead Reduction Techniques for Shared Accelerators in an MPSoC with a Ring NoC.

Vocke, Tom (2015) An evaluation of the Adapteva Epiphany Many-Core Architecture.

Abreha, Gebremedhin Teklemariam (2014) An environmental audio-based context recognition system using smartphones.

Bos, J.C.H. (2014) Synthesizable Specification of a VLIW Processor in the Functional Hardware Description Language CλaSH.

Bronkhorst, T.A.W. (2014) Hardware design of a cooperative adaptive cruise control system using a functional programming language.

Duraisingam, Prithivi Ram (2014) Crack detection in semiconductor products : machine vision techniques for detection of cracks in semiconductor products.

Elderen, Sybren van (2014) Beating Logic: Dependent types with time for synchronous circuits.

Groenhuis, Vincent (2014) Improving Accuracy and Efficiency in MRI-navigated Breast Biopsy.

Heling, Yoran (2014) Biased Random Periodic Switching in Direct Connect.

Jin, Xiaopeng (2014) Implementation of the MUSIC Algorithm in CλaSH.

Jong, Berend J.M. de (2014) A basis for the next VHDL revision.

Karuppiah Ramachandran, Vignesh Raja (2014) Characterization of Communication Mechanisms for Implantable Body Sensor Networks.

Krist, J.O. (2014) The effect of residential storage and conrrol on the distribution net compared to central storage and control.

Mosheuvel, J. (2014) Full spectrum receiver design : a case study of direct RF sampling.

Nee, F.D. van (2014) To a new hardware design methodology : a case study of the cochlea model.

Permatasari, Siti Intan (2014) Rethinking energy conservation via anevaluation of the heating system: A Case Study of Zilverling, University of Twente.

Tjhin, Yoppy (2014) DOA Estimation of UHF RFID Tags in Multipath Environments.

Wevers, Gerben G.A. (2014) Hardware Accelerator Sharing within an MPSoC with a connectionless NoC.

Warmer, Martin (2011) Detection of web based command & control channels.

Hettinga, S. (2010) Performance analysis for embedded software design.

Houtman, J. (2009) Bringing scalability/failover to a complex producer/consumer implementation.

Jeckmans, A.J.P. (2009) Practical Client Puzzle from Repeated Squaring.

Kooijman, M. (2009) Haskell as a higher order structural hardware description language.

Kuperus, Johan (2009) Wave monitoring using wireless sensor nodes.

Lukkien, Mechiel (2007) Venti analysis and memventi implementation: Designing a trace-based simulator and implementing a venti with in-memory index.

Sisseren, B. van (2007) Design of a lightweight real-time streaming kernel.

Witteman, M.T. (2007) Efficient proximity detection among mobile clients using the GSM network.

Burgwal, M.D. (2005) Serving the Montium : design of an energy-efficient processor-network interface.

MSc Embedded Systems

The master's programme in Embedded Systems provides a thorough understanding of Embedded Systems and specialisation in a specific area covering theoretical and practical aspects of embedded systems development. Students gain engineering skills and learn integration of software and hardware, system design, integration, verification and management. Graduates have the expertise to harness the possibilities for innovation in the growing area of embedded systems.

Application deadlines for studies starting 2024

16 October (2023): Application opens 15 January: Last day to apply 1 February: Submit documents and, if required, pay application fee 21 March: Admission results announced August: Arrival and study start

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Embedded Systems at KTH

Embedded systems are the most common form of computer systems, utilising around 98% of all manufactured processors for their applications, from sewing machines and cars to satellites and power plants. The common denominator for these systems is high-level demands on functionality and reliability—the master's programme in Embedded Systems fosters highly competitive graduates in this critical field.

The master's programme in Embedded Systems provides a broad education in embedded systems with the opportunity to specialise in areas that cover theoretical and practical aspects of embedded systems development. We place particular emphasis on engineering skills, integration of software and hardware, system design, integration, verification and the management of the design process.

The programme offers three tracks:

The Embedded Electronics track addresses the problems of integrating sensors, analogue circuits, and communication devices into SoC/ASIC and PCB-based embedded systems, with a focus on the Internet of things.
The Embedded Platforms track addresses the problems of designing and assembling an embedded single-/multi-/many-core CPU platform, including VLSI design and embedded software.
The Embedded Software track addresses the problems of designing and maintaining embedded software running on single-/multi-/many-core systems, including software engineering and computer hardware fundamentals.

The programme has a total of 120 ECTS credits structured as follows. About 30 ECTS credits consist of mandatory courses for all students in the programme. About 30 ECTS credits consist of courses that are mandatory for that specific track. About 30 ECTS credits are elective courses, and the final 30 ECTS credits consist of the degree project. During the last semester, you demonstrate the skills you have acquired during the programme through a degree project. You will write a thesis report, present it and defend the results. The focus of the project may be proposed by you, an examiner, a company, a public agency or any other external organisation, but the project plan must be approved by the examiner of one of the thesis project courses in the curriculum. The degree project can also be carried out at another university or a company.

This is a two-year programme (120 ECTS credits) given in English. Graduates are awarded the degree of Master of Science. The programme has courses both at KTH's main campus and KTH Kista campus in Stockholm and is offered by the School of Electrical Engineering and Computer Science (at KTH).

Programme Presentation

In this recording from October 2023, you will learn everything about the master's programme in Embedded Systems. Programme Director Zhonghai Lu and student Francesco host the webinar.

Topics covered

Embedded systems, Embedded intelligence, Digital design and validation with HDLs, Embedded hardware design in ASIC and FPGA, Computer systems architecture, Embedded many-core architectures, Hardware architectures for deep learning, Hardware security, electronic systems design, Fundamentals of integrated electronics, Embedded software, Software reliability, Methods in software engineering.

Courses in the programme

Find out what students from the programme think about their time at KTH.

"KTH focuses more on the practical aspect instead of the theoretical. There will be many assignments and seminars during the lecture period that will help you keep track of the topics covered."

Francesco from Italy

Meet the students

The enormous price and performance developments of electronics, coupled with their flexibility and programmability, create considerable opportunities for innovation. At the same time, the industry is experiencing problems with sustaining competence in the area and facing significant challenges in managing the integration of software and hardware.

Employers of graduates from the master's programme in Embedded Systems are companies that develop electronic components and embedded systems in all possible areas. The programme has a broad industrial contact network through ICES – the KTH Innovative Centre for Embedded Systems. ICES member companies support implementation and student activities in the programme, such as trainee positions, master's degree projects and pilot projects, offering participants an excellent bridge into the industry or further education in the form of doctoral studies.

After graduation

Hardware design engineer, embedded software engineer, consultant, developer, programmer, project management, CTO, R&D engineer, industrial expert, industrial management, startup founder, researcher, Doctoral students in related areas.

"I would say the best thing about KTH is the professors, and their willingness to help you out. You can always email them your questions, or even book appointments to meet and discuss further. You are never met with a negative response."

Charlene Sequeira, Cybercom

Meet the graduates

Sustainable development

Graduates from KTH have the knowledge and tools for moving society in a more sustainable direction, as sustainable development is an integral part of all programmes. The three key sustainable development goals addressed by the master's programme in Embedded Systems are:

You will acquire a fundamental understanding of the power and energy consumption of transistor-based electronic and computer systems and knowledge of basic principles for improving and optimising their power and energy efficiency in performance, cost and reliability constraints for electronic consumer products, mobile computing devices, network and communication systems, the Internet of Things and cloud computing infrastructures. Multiple courses, from theory to practice, from mini-project to degree project, allow our students to develop relevant expertise continuously.

You will be able to work as an engineer in companies that develop power- and energy-efficient solutions for electronic and embedded computing systems, a manager in organisations that provide energy-efficient IT solutions in healthcare, economic and industrial sectors, or a researcher in institutions that conduct cutting-edge research on emerging and future sustainable electronics, computers and networked systems.

Faculty and research

The master's programme in Embedded Systems is offered by the School of Electrical Engineering and Computer Science at KTH. Embedded Systems is within the subject of Electrical and Electronic Engineering, for which KTH is globally ranked 23 rd in the QS World University Rankings by Subject 2023.

Professor Zhonghai Lu is the programme director. The programme is coordinated via the Division of Electronics and Embedded Systems, Department of Electrical Engineering.

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Embedded Systems Design Laboratory

Computer science | faculty of engineering, lth, master thesis proposals, routing and scheduling for time-sensitive networks.

(Announced April 3, 2017)

A large class of embedded applications are dependent on predictable communications for accurate control (automotive, avionics) while also requiring enough bandwidth for less critical software (multimedia streaming). Time-Sensitive Networking is a set of standards under development by IEEE 802.1, which are becoming increasingly attractive for applications requiring connections with low-latency, high-bandwidth and availability. Three traffic classes are specified by TSN, namely time-triggered (TT), constrained bandwidth (CB), and best effort (BE), all providing support for a varying grade of criticality. The most critical, TT, requires careful routing and scheduling in order to meet the application demands. The goal of this project is to propose routing and scheduling tools for the TT and CB traffic, for a predefined network topology and application set. The applications will be taken from the streaming domain, where throughput is more important than latency, but latency is also constrained. One direction is to use constraint programming to define and solve the problem, but heuristics or integer linear programing may also be of use.

Prerequisites : 2 students. Knowledge of constraint programming or other optimization techniques is highly recommended. Some knowledge of packet switched networks (Ethernet), routing and scheduling techniques is a big plus.

References:

Time - Sensitive networking task Group: http://www.ieee802.org/1/pages/tsn.html
M. L. Raagaard, "Algorithms for the Optimization of Safety-Critical Networks", DTU M.Sc, Jan 2017.
JaCoP - Java Constraint Programming solver: http://jacopapi.osolpro.com

Contact person : Flavius Gruian

Software-defined Networking for Streaming Applications

Software Defined Networks have been proposed as a way of virtualizing networks, the same way hypervisors can be used to virtualize hardware platforms. Streaming applications, defined as a communicating network of actors could benefit from abstracting their underlying communication infrastructure in several ways. For instance, actor mobility across processing nodes could be made transparent to the actors, by reconfiguring the network. OpenFlow (Open Networking Forum) is a protocol for SDN that seems to gain momentum, and several switches implementing it are already available for use. The goal of this project is to examine how OpenFlow can be used in the context of streaming applications, in particular for virtualizing the communication structure of the application. Further, assuming some mobility of functionality, examine how the reconfiguration of the network can be carried out, without significantly affecting the functionality or performance of the application.

In practice this would imply:

proposing a method to program/configure the network for a given distribution of functionality (actors on nodes)
evaluating the performance of the solution with SDN compared to a standard dynamic routing network
a method for reconfiguring/updating the network when an actor moves to a different node
evaluating the impact on performance of the reconfiguration

Prerequisites : 2 students. Knowledge of optimization techniques and C-programming is highly recommended. Knowledge of packet switched networks, routing and scheduling is a plus.

References :

OpenFlow website: https://www.opennetworking.org/sdn-resources/openflow
Durner, R., Blenk, A. and Kellerer, W., 2015, June. Performance study of dynamic QoS management for OpenFlow-enabled SDN switches. In Quality of Service (IWQoS), 2015 IEEE 23rd International Symposium on (pp. 177-182). IEEE.
Eker, J. and Janneck, J., 2003. CAL language report (Vol. 3). Tech. Rep. ERL Technical Memo UCB/ERL.

Using the CAL data flow language as an input specification for a modem programming flow.

In order to deliver high quality output, modems have tight real-time requirements, typically defined in terms of minimum guaranteed throughput and/or maximum latency.

Embedded platforms for modems are expected to handle several streams at the same time, each with its own rate. Typically, functionality can be divided in jobs, i.e. minimal groups of communicating tasks that are started and stopped independently. The number of use-cases (i.e. combinations of simultaneously executing job instances) can be high.

In the approach being studied at ST-Ericsson in Eindhoven, the Netherlands, modem transceivers are modeled as data flow graphs [1].

The target hardware platform is a heterogeneous Multiprocessor System-On-Chip (MPSoC).

On an MPSoC, transceivers share computation, storage, and communication resources. This poses a particularly difficult problem for the scheduling of real-time applications: resource sharing leads to uncertainty about resource provision, and, consequently, uncertainty of the temporal behavior.

The overall scheduling strategy proposed at ST-Ericsson [2] for this system mixes static (compile-time) and dynamic techniques (run time).

Intra-job scheduling (i.e scheduling of tasks that belong to the same job) is handled by means of static order, i.e., per job and per processor, a static ordering of actors is found that respects the Real-Time requirements while trying to minimize processor usage. Inter-job scheduling is handled by means of local Time Division Multiplex (TDM) schedulers: per job and per processor a slice time duration S is allocated.

A tool is available that performs both mapping and temporal analysis of the mapped application.

A weakness of the current approach is that the data flow model is generated manually, upon studying the actual application code. This means that the model may not actually conform to the actual implementation.

To bridge this gap between modeling and implementation, the model should be automatically extracted from the implementation code. For this to be possible, the implementation has to be specified in data flow.

CAL is a domain-specific language that provides useful abstractions for dataflow programming with actors. CAL has been used in a wide variety of applications and has been compiled to hardware and software implementations, and work on mixed HW/SW implementations is under way.

The goals of this project are:

To show that CAL can be used to specify the inter-task communication behavior of a radio application running on an ST-Ericsson platform: this can be done by either adapting an existing radio implementation in CAL to the ST-Ericsson multiprocessor, or by re-implementing the task communication in an existing implementation of a radio application in the ST-Ericsson multiprocessor;
To show that a data flow analysis model can be generated from the CAL specification, and that this model can be analyzed by ST-Ericsson's data flow analysis tools;
To show that the CAL specification of the inter-task communication behavior can reuse algorithms already coded in C, using core intrinsics
To show that code using the ST-Ericsson runtime can be generated from the CAL specification.

The applicant preferably has a background in computer science, basic knowledge about signal processing, as well as good insights into compiler technology and embedded systems.

The work is to be carried outing two phases: a first phase in Lund, for familiarization with the CAL language and associated tooling, And a second phase at the ST-Ericsson unit in Eindhoven, The Netherlands, for a minimum period of 6 months, under the local supervision of Orlando Moreira.

During the stay in Eindhoven, ST-Ericsson will grant a montlhy allowance to the applicant, to help with the costs of living in the Netherlands.

[1] E. Lee and D. Messerschmitt “Synchronous Data Flow”, Proceedings of the IEEE, 1987

[2] O. Moreira, F. Pereira, and M. Bekooij, “Scheduling Multiple Independent Hard-Real-Time Jobs on a Heterogeneous Multiprocessor”, Proceedings of the ACM Embedded Software (EMSOFT) Conference, Salzburg, Austria, 2007

[2] O. Moreira, et al, “Online Resource Management for a multiprocessor with a network-on-chip”, Proceedings of the ACM Symposium on Applied Computing, 2007

Contact person: Jörn W. Janneck

Global constraints in JaCoP (several project proposals)

This is the set of projects that have a common aim to develop different global constraints for Open Source Java Constraint Programming solver ( JaCoP ). This solver is written entirely in Java and provides a broad selection of constraints and search methods. Constraint programming over finite domain offers an elegant way of modeling and solving combinatorial problems but for efficiency reasons needs global constraints that encapsulate specific reasoning algorithms. These algorithms makes the modeling and solving easier. The goal of a project in this area is to develop and test one global constraints. The possible candidates for the project include (but are not limited to):

Smart table constraint [1],
Tree constraint (specific graph constraints) [2].

To carry out the project a good understanding of constraint programming paradigm is required. Preferably the student should have studied EDAN01 Constraint Programming course.

[1] Jean-Baptiste Mairy, Yves Deville, and Christophe Lecoutre, "The Smart Table Constraint", International Conference on AI and OR Techniques in Constriant Programming for Combinatorial Optimization, 2015.

[2] Nicolas Beldiceanu, Pierre Flener, and Xavier Lorca, "The tree Constraint", International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming, 2005.

Contact person: Kris Kuchcinski

Sidöversikt

Research group sites.

Computer Graphics
Embedded Systems Design
Robotics and Semantic Systems
Software Engineering Research Group
Software Development and Environments

Research Area Sites

Artificial Intelligence
Natural Language Processing
Robotics and Automation Software

Research Project Sites

Software and community sites.

Accessibility Statement

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Embedded Systems Engineering

Module Catalog for

Curated list of available modules for the specialization. For students of year 2019 and further (PO 2019).

As described on the general curriculum page , all specializations follow the same structure only differing in the catalog of modules to choose from. The tables below show a curated listing of modules for your convenience, but the official module handbook on c @ mpus always takes precedence.

Every specialization involves:

1 Basic Module (6CP)

10 Specialization Modules (each 6CP = 60CP) in roughly equal parts from computer science (CS) and electrical engineering (EE):

2+ Core Modules from each CS and EE for a total of 30CP
2+ Supplementary Modules from each CS and EE for a total of 30CP

1 Research Project (15CP) The project may be replaced with a Seminar (3CP) plus two additional choices from the full catalog of core and supplementary modules (each 6CP)

1 Lab Course (6CP)
1 Non-Technical Module (3CP)
1 Master Thesis (30CP)

There is a small set of supplementary modules that are only worth 3CP. A maximum of two 3CP modules can be picked for your studies, replacing one 6CP supplementary module.

Supplementary Modules recommended for the 1. semester are marked with ⭐ .

Basic Module

Core modules - computer science.

Choose 2-3:

Core Modules - Electrical Engineering

Supplementary modules - computer science, supplementary modules with reduced ects (3cp), supplementary modules - electrical engineering, research project / seminar.

The research project is a larger experimental or theoretical work graded after a written report. It equals a workload of 15 credit points (3 months or 450 hours) to be carried out over one semester, preferably at a university institute, or (with additional restrictions, see attached information sheets) at an external institution. It is meant to give the opportunity to apply theoretical knowledge practically as a preparation for the master thesis. If no suitable topic is found, the project may be replaced by a seminar and two additional specialization modules (core or supplementary modules). A project report (in english) and a presentation of 20-30 minutes conclude the examination.

More information on the Research Project

A seminar is only pickable as replacement for the research project! A seminar and two additonal choices from the core or supplementary catalogs replace the project. More information on the general curriculum page .

The listed modules are only the seminars that are permanently registered in c @ mpus. All seminars offered in english by the institutes of the departments of computer science and electrical engineering, that do not explicitly exclude infotech students, can be registered under the generic module Seminar INFOTECH by explicitly selecting the examiner during exam registration. For seminars offered by the CS department a special registration is held, which is announced during the preceding semester. For other seminars you might have to register with the professor or institute directly as they organize the seminars on a changing per-semester basis. In any case the seminar still has to be registered again with the examination office to receive a mark!

Lab Courses

Non-technical modules.

European Master in Embedded Computing Systems

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Curriculum and degree

EMECS is a two-years master’s program. A total of 120 ECTS (European Credit Transfer and Accumulations System) credit points must be acquired. The curriculum consists of a core program, an elective program and a Master’s Thesis. The core program covers the fundamentals of embedded computing systems and offers an equivalent education in all four institutions. The elective program reflects the specific profiles of the participating partner universities and their associated research institutes.

All EMECS students who have successfully completed the curriculum will

have a profound understanding of the scientific underpinning of the Embedded System field

be familiar with state-of-the-art architectures of hardware and software systems and how these architectures have different characteristics in different application domains and Embedded Systems ecosystems

have competences in creating new architectures for hardware and for system software (operating systems), including new and evolving architectures for Embedded Intelligence

be familiar with design methodologies for Embedded Systems

have knowledge of design models, languages and techniques for all levels of the design process of Embedded Systems

be familiar with the requirements of dependability and security for Embedded Systems and how these requirements are addressed at different levels of the design process

have practical skills in the development of embedded software

have practical skills in using state-of-the-art computer-aided methods and tools for hardware design, test and verification

have hands-on experience in industry-related embedded systems projects.

Master of Science (M.Sc.) in Embedded Computing Systems (Joint Degree or Double Degree)

Core Program (45 ECTS)

The core program consists of three study areas:

Embedded System Hardware Architectures

System Software

System-on-Chip (SoC) Design Methodology

The four partner universities have agreed on the contents of these core study areas. All teaching modules of the core program are mandatory to all students and need to be finished within the first year of study at one of the partner universities. The core program guarantees that all students can achieve an equivalent educational level regarding the basic principles of embedded system design and architecture. After completion of the core program, no matter at which partner institution, students will be able to take full profit of the elective program and project activities offered throughout the consortium.

More information: TUK , NTNU , UoS , POLITO

Elective Program (45 ECTS)

The elective program consists of five study areas:

Advanced Topics in Embedded Systems

Communication & Signal Processing

Automation & Control

Microsystems

Artificial Intelligence

These areas are offered by all partner universities. Each partner university contributes a number of teaching modules to each elective study area. The teaching modules within an elective study area are varying between universities and reflect specific local strengths, special application areas, design methodologies and architectures of embedded systems.

There are no mandatory teaching modules in the elective program. Every student is assigned a supervisor at each of the two partner universities that he or she attends. Based on the elective program an individual study plan is elaborated and mutually agreed on between the student and the supervisors.

Master’s Thesis (30 ECTS)

The last part of the curriculum during the second year of study is dedicated to a Master’s thesis. A thesis topic can be chosen at any partner institution of the consortium. The Master’s thesis is typically embedded into larger research projects conducted by the local research centres or together with industry. The topic and location of the Master's thesis is determined during the second year of studies.

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TEC - Computer Engineering Group

Seminar: advanced topics in networked embedded systems, information on the coronavirus.

The ETH task force headed by the Vice President for Infrastructure is monitoring developments in the coronavirus pandemic and will continue to draw up suitable measures as necessary. You can find constantly updated information on the coronavirus web page.

To ETH's coronavirus web page

Spring Semester 2022

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The seminar will take place physicall in room ETZ G 71.2 .

The seminar covers advanced topics in networked embedded systems. A particular focus are cyber-physical systems and sensor networks in various application domains. The goal is to get a deeper understanding on leading edge technologies in the discipline, on classes of applications, and on current as well as future research directions.

The seminar enables master students, PhDs and postdocs to learn about latest breakthroughs in embedded information processing including machine learning, wireless sensor networks, networked embedded systems and devices, and energy-harvesting in several application domains, including environmental monitoring, tracking, smart buildings and control. Participants are requested to actively participate in the organization and preparation of the seminar.

Topics and Schedule

The papers to choose from are listed below. Papers with associated presenters are already taken.

Participation

To get credit points for the seminar, you must read and review all papers we discuss at the semester. The deadline for a paper review is always on Friday (end of the day) before the seminar when the paper is being presented and discussed. The reviews must be submitted to our review submission system . You need a user account to submit your reviews and to read reviews of others after you have submitted yours. A user account will be created after you sign up for the seminar and send us the title of the paper you wish to present. While reading and reviewing scientific papers, you develop and train your skills at critical thinking and scientific writing. Try to be as critical as you can when reading a paper and take notes. Use your notes to summarize the critical points in a review. When writing a review: be constructive, structure your thoughts, suggest how to improve the paper. You might want to check the tutorials how to review and external page how NOT to review call_made a paper before you start.

Presentations and Discussion

There is one participant responsible for a each of the papers. We expect you to give a conference style presentation of papers (15 minutes). You may want to contact paper authors and ask them for slides. If the slides are not available, you can copy relevant parts of the paper from a PDF and present the paper with your own words and pictures. You can decide on the presentation style yourself, but consider using the seminar as an opportunity to improve your presentation skills.

Assume that the seminar participants know nothing about the paper, but are knowledgeable in the overall field. We do not expect you to present the whole paper in every detail, but the motivation and the main contribution of the paper must be covered in your presentation. Please spend some time rehearsing your talk before the seminar and stay within the time limit. Your slides and talk should be in English and your presentation should last about 15 minutes plus 5 minutes questions and answers directly to the technical contents of the paper.

After the presentation of the paper and the technical Q&A session, the presenter should provide a short summary of the reviews. Afterwards you should lead a lively discussion on the presented paper. For example, the presenter may shortly present paper strengths and weaknesses in terms of writing style and technical contents or list several open questions based on the results of the paper. You may also discuss possibilities fo future research in the area, for example a title and a proposal for a typical Master Thesis at ETH.

Students' attendance of all seminar sessions and active participation in the discussion is expected. To successfully pass the seminar and get credit points, you must read and review all papers discussed in the seminar and have the role of a presenter for one of the papers.

Organization

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Master thesis projects

Finding a thesis project.

For students participating in the TU Delft computer science and embedded systems master’s programs we have several openings for research thesis projects. Usually these topics can also be adjusted to fit in the scope of a BSc research project.

All MSc projects are aligned with our research. They often are connected to one of our ongoing research projects , but we also frequently use MSc projects to explore new research directions. Projects can be conducted at:

TU Delft in our own research labs, in close collaboration with our postdocs and PhD students
Industry (as part of an internship), usually with companies (in The Netherlands or abroad) with which we have an ongoing research collaboration (e.g. ING, SIG, Adyen, ATOS, XWiki, Microsoft, Google, Facebook, Infotron, JetBrains, …)
Other (international) universities – we have a rich network of academic friends around the world.

If you study at a different university and you would like to write a research master thesis in the context of one of the SERG projects, you should ask your own university supervisor to contact us. We have limited places available, but are always interested in new research opportunities.

SERG Supervisors

You can make an appointment with one of the SERG group members to see what projects are currently open, or you can propose your own project, provided there is a clear connection with the research we conduct at our labs. You can contact the following persons for more information:

Composing your Study Program

If you plan to conduct your MSc project at SERG, you will need to include at least two of the CS MSc courses SERG teaches in your IEP (Individual Exam Program). We strongly recommend you to follow our software architecture, software analytics, or software testing and reverse engineering courses. Besides our own software engineering related courses, when choosing the electives in your program you can consider including courses in such areas as machine learning, computational intelligence, data science, compiler construction, distributed systems, or security.

Optionally, you can start your research with a 7-8 week literature survey (IN4306, 10EC). This assignment is concluded with a report containing an overview of the state-of-the-art in a particular branch of research.

Proposing your Own Project

Under certain conditions it can also be possible to propose your own project. In those cases it is important to

Study a number of existing MSc theses .
Identify an ongoing research project to which your proposal is connected.

In particular you need to carefully think about the research component of your proposal, and have a clear idea on why your proposal is novel – it should advance the world’s knowledge in software engineering. If you wish to pursue this route it is advisable to select and contact a possible supervisor as early as possible.

Writing your Thesis

Once you’ve found your project and your supervisor, we recommend that you start writing as soon as possible: Devise a table of content, and fill in details as you go.

To write your thesis you need to make use of our MSc Thesis Template .

CHE University Ranking
DAAD database on admission requirements
Help and Advice

International Programmes 2023/2024

Embedded Systems Design Embedded Systems Design

Bremerhaven university of applied sciences • bremerhaven.

Course details
Costs / Funding
Requirements / Registration

The courses are held in English.

Applicants with a non-European Bachelor's degree are required to start the application process via uni-assist . Please consider the set deadlines: Summer semester: 31 December More information can be found on our website .

Applicants with a European Bachelor's degree can find the complete application procedure here:

Application procedure

Summer semester: 15 February

Embedded systems are regarded as a key technology for new industrial, scientific, and medical devices. From domestic devices like washing machines to complex space technology such as satellites, most products require integrated digital control and software. These components have a great impact on functionality and performance. With more than 16 billion devices, embedded systems are everywhere. As "hidden systems", the embedded systems determine innovations in industrial equipment, medical devices, and scientific instruments. Since many products without embedded systems cannot compete on the market, specially trained personnel are demanded by the industry worldwide.

Bremerhaven University of Applied Sciences recognises these demands and offers a new Master's study programme Embedded Systems Design (ESD). An embedded system in the scope of ESD is a system whereby a mechanical or electromechanical system receives its essential functionality via electronics, control, and software. Courses like system identification, mechatronics, and discrete control systems qualify students to design future embedded systems in industrial, medical, or scientific applications (ISM market). ESD pays attention to system-on-chip (SoC) solutions using programmable digital devices. The graduate students will meet the challenge of designing modern, safe, and reliable embedded products.

Requirements: engineering is an integral part of ESD.

Applicants should be interested in control engineering, mechanics, programmable logic systems (FPGAs), and software development. Basic knowledge in these areas, as well as sound engineering principles of a preceding technical Bachelor's degree, are requirements for admission to the ESD Master's programme.

The first semester of Embedded Systems Design teaches methods required to engineer embedded systems:

Mechatronics
Discrete Control Systems
Digital Systems / VHDL
System-on-Chip Design
Model-based Real-time Software Development
Safety and Reliability Engineering

The second semester is more application-oriented:

Industrial Systems
Medical Systems
Maritime Scientific Instruments
Requirements Engineering
Embedded Systems Design Project

The modules consist of class and lab parts. The lab sections increase over time from 25% to 75% to transfer theory to practical applications.

The Master's thesis and the defence colloquium are intended for the third semester. Master's thesis topics comprise university research projects or industrial development/research.

All classes and labs as well as course documentation and exams are in English.

Part-time study is possible according to the part-time study regulations of Bremerhaven University of Applied Sciences. Part-time study must be motivated and approved by the university. A common reason for part-time study is professional work in the area of embedded systems.

No industry internship is required for the Embedded Systems Design Master's degree.

343 EUR (winter semester 2022/2023) The fee includes a semester ticket covering public transport in the Bremerhaven and Bremen metropolitan areas.

Living costs in Bremerhaven are rather low in comparison to other German cities. The estimated amount of 800 to 900 EUR per month should be sufficient to cover basic expenditures. However, the amount of money spent by the student strongly depends on his or her own standard of living. Here is a rough estimation of monthly costs: health insurance: 100 EUR (for non-EU applicants), rent: 250 to 350 EUR, food and other costs: 350 to 450 EUR.

Bachelor's degree (or equivalent academic degree) in a technical subject with knowledge in

Electrical engineering
Mathematics/physics
Basics of mechanics
Control engineering
Digital systems
Programming/software

The final grade for the Bachelor's degree must be "good" (German grade 2.3, CGPA of 2.7 out of 4.0 or equivalent). For applicants with a professional background of two years or more after their Bachelor's degree, the required grade increases to 2.6. A transcript of records must be submitted with the application to verify that the admission requirements are satisfied.

Applicants must provide proof of their English and basic German language skills.

English: level B2 according to CEFR (Common European Framework of Reference) TOEFL iBT 72 (Internet-based), IELTS (band score) 6.0 or a preceding Bachelor's study programme taught in English

German: level A1 according to CEFR (the lowest level)

Hochschule Bremerhaven c/o uni-assist e.V. 11507 Berlin Germany

Students may work up to 120 days (or 240 half days) per year. The university offers student jobs (student tutor, lab assistant, etc.) currently at a rate of 12.29 EUR per hour.

Accommodation is available through the Student Service Office ( Studierendenwerk Bremen ) or on the private market. A single or two-room flat costs approx. 200 to 240 EUR. Private accommodation can be found online:

International Office
ASTA Bremerhaven
Specialist counselling
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Support with registration procedures

Bremerhaven University of Applied Sciences

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Bicycle pedal for the 21st century

Embedded Systems Engineering (Master of Science)

Embedded systems are among the key technologies. Whether in medical technology, the automotive industry, in aerospace or in the telecommunications, media and entertainment technology - embedded systems play a central role in the latest technological developments. The systems that "feel" with sensors, "think" through intelligent programming, and "act" on signals and actuators perform a wide variety of tasks.

Connection between engineering and computer science

In the master's program, we provide you with versatile know-how in computer science and engineering. For your future as a research scientist or project leader in a company, you are well equipped to understand and bring together the "language" of both worlds of technology.

You will gain knowledge about the design of microelectronic, micro-mechanic and software-based components as well as their integration into complete systems. An extensive selection of courses allows you to set an individual focus or specialize in one of the following areas:

Artificial Intelligence

Cyber-Physical Systems

Circuits and Systems

Materials and Fabrication

Biomedical Engineering

Prerequisites

Bachelor's degree in mechatronics, information technology, electronics or electrical engineering, computer science or similar. Previous knowledge in mathematics, computer science, physics and electrical engineering
English language proficiency level C1 (to find out which language certificates are excepted, please go to Application / English language proficiency).

Facts and Figures

Fees and cost, application.

Students can compile their own personal skill profile by either selecting a wide range of different courses from either Computer Science or Microsystems Engineering to broaden their expertise. Or they can choose to focus on a specialization in either one of the Computer Science areas (Artificial Intelligence or Cyber-Physical Systems) or one of the MSE concentrations (Circuits and Systems, Materials and Fabrication, Biomedical Engineering and Photonics).

The course structure is quite versatile and the exam regulations only provide the framework, which students fill with individually chosen lectures, seminars and other courses. There are 4 compulsory areas where students are expected to complete courses with at least 18 ECTS credits in each area: 2 areas cover essential courses for the topic of Embedded Systems divided in Computer Science respectively Microsystems Engineering; 2 more areas contain specialization and concentration courses in both the Elective area of Computer Science as well as MSE concentration areas. The remaining 18 ECTS credits can be divided up as the students wish, by either adding more courses in one of the 4 areas mentioned above or completing some courses in the Customized Course Selection. The program concludes with a master's thesis.

The following graphic summarizes the structure:

This example of an individually structured study plan for an assumed start in the winter semester can provide a starting aid for building your own study plan.

Students who want to obtain a Master of Science degree in Embedded Systems Engineering with a specialization in one of the areas, have to choose courses amounting to at least 30 ECTS credits as well as the topic of their master thesis from the respective field.

For Cyber-Physical Systems (CPS), the related courses are listed here: Lectures Specialization CPS - Vorlesungen Spezialisierung CPS (PDF)

For Artificial Intelligence (AI), the related courses are listed here: Lectures Specialization AI - Vorlesungen Spezialisierung KI (PDF)

For a specialization in one of the MSE areas (Circuits and Systems, Materials and Fabrication, Biomedical Engineering or Photonics), students can choose from the modules assigned to the respective area.

Organizational note for students of the previous exam regulations (PO 2012):

In the winter semester 2021/22, a new examination regulation has been introduced and all students who did not explicitly object by September 15, 2021 (legally latest deadline: October 31, 2021) have been automatically transferred to this new examination regulation PO 2021. For interested students we offer some information material comparing the examination regulations (document updated on April 12, 2022 with further explanations regarding Customized Course Selection).

The changes have different implications for individual students. If you have any questions, please contact the academic advisor.

Students of the PO 2012 version can complete their studies until 30 September 2024 (cut-off date) at the latest. The model study plan / curriculum for the PO 2012 exam regulations can be found on the overview page Module Handbooks and Exam Regulations .

Possible occupational fields

Graduates of the Master's program in Embedded Systems Engineering can either apply for a PhD position or work as an engineer in a company. Potential employers are companies from the following fields:

Automotive industry
Bio- and medical engineering (e.g. prosthetics or implants)
Communication

Syllabus and Examination Regulations

Please note: Only the latest versions are listed here. Older versions can be found in Module Handbooks and Exam Regulations under Studies and Teaching.

Online version of the module handbook in HISinOne (Please note, loading might take some time)

Detailed PDF version of the module handbook (as of March 2024) (Please note: the PDF version is updated only once per semester)

Exam and admission regulations (in German) The web pages of the legal department contain all statutes (admission and examination regulations). The latest version applies to you, i.e. the one without further explanation/restriction in brackets. S tudents who started their studies before WS 2021/22 can find the respective information under Module Handbooks and Exam Regulations under Studies and Teaching
Exam regulations (unofficial version in English - not binding)

Please check out our dates and deadlines for course registration or exam registration.

Contact Persons

Do you have any questions concerning the application and admission procedure? Please contact the program coordinator:

For questions pertaining to the curriculum, please contact the academic advisors:

Testimonial

Titus Busulwa

Particularities about this study program

Numerous lab courses.

The students can choose from a big variety of lab courses within the MSE Concentration areas or in the Customized Course Selection (in the area of Computer Science), thus acquiring important practical skills for their future career.

A Mentor for each Student

Each professor is in charge of a number of students whom s/he mentors. These mentors help you to organize your studies and are ready to answer your questions about studying abroad, finding a job, and more.

Certification of English Medium of Instruction Competencies

Smart, Micro, Green – Engineering in Freiburg

Green - Freiburg is renowned worldwide as a Green City. Since 2015, the Faculty of Engineering has had its own Department of Sustainable Systems Engineering. The researchers of this department build systems that hardly need any energy, have a long life cycle, and adapt themselves easily to difficult environmental conditions. Smart - stands for autonomously acting robots, computers that learn to interpret pictures, or algorithms that become more and more intelligent and fast. In summary: At the Faculty of Engineering, smart stands for computer science. Micro - Our researchers design tiny technical systems that handle complex tasks needed in medicine or in production plants. Nowadays each of us uses such systems on a daily basis - often without even noticing. Developing microsystems is an exciting and challenging job - not only for students but also for companies. Our study programs are the best preparation for a career in this field. Studying engineering in Freiburg means that you will benefit from these three research areas, no matter which study field you choose. Smart, micro and green ideas will increasingly be needed. We offer to teach you the skills needed for developing these kinds of systems.

Further Information

How to prepare your stay in Freiburg - Information for admitted students
Website of the Department of Microsystems Engineering
Website of the Department of Computer Science
Orientation Manual for new MSc. ESE students
Overview with some important (administrative) informations for new students

IMAGES

Embedded System thesis topics
PPT
Masters in Embedded Systems
Embedded System Thesis topics and Research Implementation Guidance
Chapter 10 Topics in Embedded Systems
PPT

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One Day Training workshop for Thesis Students Towards selection of Thesis Project

COMMENTS

Embedded Systems Research Topics Ideas
List of Research Topics and Ideas of Embedded Systems for MS and Ph.D. Thesis. Embedded system design: embedded systems foundations of cyber-physical systems, and the internet of things. Jetset: Targeted firmware rehosting for embedded systems. Time-Sensitive Networking in automotive embedded systems: State of the art and research opportunities.
Embedded Systems Project Topics With Abstracts and Base Papers 2024
Embark on a transformative journey into the world of embedded systems with our meticulously curated selection of M.Tech project topics for 2024, thoughtfully complemented by trending IEEE base papers. These projects encapsulate the forefront of innovation and challenges in embedded systems, offering an indispensable resource for M.Tech students seeking to delve into the dynamic landscape of ...
15+ Latest Research Topics in Embedded Systems for PhD Scholars
NS2. The amalgamation of software and hardware in a computer system is called an embedded system. The signal processors, microprocessors, and digital signal processors are functioning through the embedded systems. In addition, flexibility, scalability, energy, dependability, efficiency, and precision are some of the notable features of embedded ...
Master theses from the Master Programme in Embedded Systems
Here you find lists of master theses written at the department for IT, by students from the Master Programme in Embedded Systems. Other programs: Master in computer science, older program, Bach. in computer science, Systems in technology and society, Msc in IT engineering, Master in computer science, Master in HCI, Master in computational ...
Theses
Theses Research / Thesis. If you want to do your research project, bachelor- or master thesis with us, please contact a potential supervisor from the list of our Ph.D. candidates via e-mail and set the address [email protected] on CC.. Further details regarding the application can be found in our ESI Wiki.. Topics
Master Theses
This shows the increasing importance of efficient Linux Power Management. The Power Management in Linux is implemented in several kernel subsystems correlating to hardware characteristics, like P-States (Frequency Scaling) and C-States (Sleep States). This thesis examines the Idle Power Management of Linux, and therefore focuses on C-States.
embedded systems Latest Research Papers
Embedded systems are increasingly used in our daily life due to their importance. They are computer platforms consisting of hardware and software. They run specific tasks to realize functional and non functional requirements. Several specific quality attributes were identified as relevant to the embedded system domain.
Programme: Embedded Systems MSc (60331)
Böhmer, Kevin (2023) Radiation resilience evaluation of a Flash-based FPGA with a soft RISC-V Core. Dadhich, Shrasti (2023) Increasing the accuracy of rodent detection and estimation of the population with emerging sensor technology. Fikse, J. (2023) Bluetooth Direction Finding using a Uniform Rectangular Array.
PDF Seminar: Advanced Topics in Networked Embedded Systems
-advanced-topics-in-networked-embedded-systems.html - Lothar Thiele, [email protected] • Language: English • Biweekly on Tuesday, 14:15 - 16:00 ... form of a typical Master Thesis project at ETH, - list several open questions on the paper to trigger a discussion, - ask a first question yourself to break the ice (writing
MSc Embedded Systems
The master's programme in Embedded Systems is offered by the School of Electrical Engineering and Computer Science at KTH. Embedded Systems is within the subject of Electrical and Electronic Engineering, for which KTH is globally ranked 23 rd in the QS World University Rankings by Subject 2023. Professor Zhonghai Lu is the programme director.
Research Topics of Embedded Systems Group
Research Topics of Embedded Systems Group. NAAICE. Data centers require large amounts of energy. In the joint project NAAICE (network-attached accelerators for energy-efficient heterogeneous computing), which started in September 2022, the Fraunhofer Heinrich-Hertz-Institut (HHI) is concerned with increasing the energy efficiency of HPC data ...
Master Thesis Proposals
A large class of embedded applications are dependent on predictable communications for accurate control (automotive, avionics) while also requiring enough bandwidth for less critical software (multimedia streaming). Time-Sensitive Networking is a set of standards under development by IEEE 802.1, which are becoming increasingly attractive for ...
Embedded Systems Engineering
Embedded Systems Engineering. ... 1 Master Thesis (30CP) There is a small set of supplementary modules that are only worth 3CP. ... It is meant to give the opportunity to apply theoretical knowledge practically as a preparation for the master thesis. If no suitable topic is found, the project may be replaced by a seminar and two additional ...
PDF Master Thesis In Embedded Computing System
Master Thesis In Embedded Computing System PORTING OF FREERTOS ON A PYTHON VIRTUAL MACHINE FOR EMBEDDED AND IOT DEVICES Supervisor : Prof. Enzo Mingozzi Co-Supervisor : Prof. Carlo Valatti Ext-Supervisor : Dr. Daniele Mazzei Student: Nisar Ahmad Academic year: 2014-2015 [2] To my Family in Pakistan, To you, Afsheen ...
Curriculum and degree
EMECS is a two-years master's program. A total of 120 ECTS (European Credit Transfer and Accumulations System) credit points must be acquired. The curriculum consists of a core program, an elective program and a Master's Thesis. The core program covers the fundamentals of embedded computing systems and offers an equivalent education in all ...
Seminar: Advanced Topics in Networked Embedded Systems
The seminar covers advanced topics in networked embedded systems. A particular focus are cyber-physical systems and sensor networks in various application domains. The goal is to get a deeper understanding on leading edge technologies in the discipline, on classes of applications, and on current as well as future research directions.
Master's Programme in Embedded Systems
Then the Master Program in Embedded Systems is right for you. The programme provides you with an in-depth education in computer and systems science for embedded systems, emphasizing software design, implementation and analysis. You will also gain skills in writing software in different development environments and programming paradigms. Autumn ...
Master Thesis Topic for Embedded Systems Engineering : r/embedded
Master Thesis Topic for Embedded Systems Engineering. I'm going to apply for Embedded Systems Engineering Master programs and they ask me to come up with the idea that I want to do research in the field. I'm interested embedded systems in e-mobility field and open to new ideas. Looking at software updates is a broad and interesting topic, the ...
Master thesis projects
Finding a Thesis Project. For students participating in the TU Delft computer science and embedded systems master's programs we have several openings for research thesis projects. Usually these topics can also be adjusted to fit in the scope of a BSc research project. All MSc projects are aligned with our research.
Embedded Systems Design Embedded Systems Design
Embedded Systems Design Project; The modules consist of class and lab parts. The lab sections increase over time from 25% to 75% to transfer theory to practical applications. The Master's thesis and the defence colloquium are intended for the third semester. Master's thesis topics comprise university research projects or industrial development ...
Embedded Systems Engineering (Master of Science)
Students who want to obtain a Master of Science degree in Embedded Systems Engineering with a specialization in one of the areas, have to choose courses amounting to at least 30 ECTS credits as well as the topic of their master thesis from the respective field. For Cyber-Physical Systems (CPS), the related courses are listed here:
Master Thesis Topic in IoT Domain for Embedded Systems Engineering
Embedded. This sub is dedicated to discussion and questions about embedded systems: "a controller programmed and controlled by a real-time operating system (RTOS) with a dedicated function within a larger mechanical or electrical system, often with real-time computing constraints." 155K Members. 268 Online. Top 1%.
31 Jobs als master thesis embedded in: Deutschland
Nach Master thesis embedded-Jobs in Deutschland mit Bewertungen und Gehältern suchen. 31 Jobs für Master thesis embedded in Deutschland. ... Knowledge of functionality and architecture of embedded systems ... Conduct in-depth research on assigned topics related to digital communication systems or embedded systems. Currently enrolled as a ...

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Master theses from the Master Programme in Embedded Systems

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Master Theses

MA : Hardware-Aware Layer Fusion of Deep Neural Networks

Hardware-Aware Layer Fusion of Deep Neural Networks

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MA : Multicore-Optimierung eines bildverarbeitenden Systems

MA : A Deep Dive into C-States, Idle Governors and the Prospects of an eBPF Idle Governor

MA : Design and Implementation of a Memory Prefetching Mechanism on an FPGA Prototype

MA : SmartNIC Enhancements for Network Node Resilience

MA : Parsimonious Semantic Segmentation Training Using Active Learning and Synthetic Data

MA : Neural Style Transfer for Synthetic Data

MA : Anomaly Detection and Active Learning for Semantic Segmentation Tasks

MA : Learning to Prune and Quantize Transformers

MA : Sparse Lookup Tables with dynamic precision adaptation for image processing on FPGA

MA : Runtime Reconfigurable Winograd-based FPGA Accelerator for CNN Inference

embedded systems Recently Published Documents

A Modular End-to-End Framework for Secure Firmware Updates on Embedded Systems

Computer development based embedded systems in precision agriculture: tools and application

Getting Started with Secure Embedded Systems

Embedded Systems and Architectures

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MSc Embedded Systems

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Software-defined Networking for Streaming Applications

Using the CAL data flow language as an input specification for a modem programming flow.

Global constraints in JaCoP (several project proposals)

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Core Program (45 ECTS)

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