Bachelor and Master projects

The Pervasive Systems group continuously investigates new and exciting research areas and there are a lot of opportunities for Masters and Bachelors students to explore new interests or consolidate foundations. Have a look below for some ideas, all the projects can be tailored for either Masters or Bachelors, For more information about the projects and to discuss your own ideas in research at Pervasive Systems, please do get in touch with our Master Project coordinator Alex Chiumento.

You have to fill in the registration form at the start of your project.

Available assignments

We do have several assignments in several technologies and application areas. Our research spans diverse domains, including optimizing sports performance and enhancing the safety of elderly individuals through wearable computing and unobtrusive sensing. We address sustainability challenges by developing smart sensing technologies to monitor environmental changes and evaluate the impact of climate change on ecosystems. Additionally, our work in smart cities leverages opportunistic sensing and mobile smartphones to tackle issues related to safety, traffic flow, and secure data sharing, contributing to the evolution of intelligent transport systems.

The student assignments have been provisionally divided into categories to make reading this page easier. In general, each category represents the application domain in which each research project can be carried out. All projects have a small header at the front specifying if the main work deals with sensing, data science, or networking. Interested students are encouraged to contact prospective supervisors to see how a topic can be adapted.

[S = Sensing,   N = Networking,   D = Data Analytics and Machine Learning] 

Humans and Health

• [DS] Making cycling safer: Exploring deep learning for cyclist emotion recognition
• [DS]Resource-Efficient Deep Learning for Mobile Activity Recognition
• [SND] Wearable system to digitize your body posture to Metaverse
• [SND] Sensor data pre-processing & compression for BLE transmission
• [DN] WiFi vs. Sensors: Face-off between physical sensors and wireless signals in human activity recognition
• [DN] WiPi: Contactless sensing using a Raspberry Pi and NEXMON
• [D] Facial Video-based rPPG Estimation
• [D] DeepFake Manipulation Detection
• [D] Language-guided Audio-Visual Source Separation

Wearable Computing

• Master Thesis Assignment: Head Gesture Recognition using the OpenEarable Platform [NEW]
• Head Gesture Recognition with Earables [NEW]
• Continuous User Authentication with Earable IMUs using Machine Learning [NEW]

Augmented Reality

• Exploring Solutions for Latency Reduction in Collaborative AR [NEW]

The Natural World: animals, plants and biodiversity

• [D] Use Everything you got

Infrastructure Monitoring

• Camera pose estimation of large infrastructure [NEW]

Wireless networks of the future

• [D,S,N] Leave me alone Wi-Fi spy!
• [N] Do Horoscopes Work for Factories? Performance Comparison of Wireless Channel Prediction Algorithms within an Indoor Factory Floor
• [N] Are Horoscopes beneficial? Sensitivity Analysis of Predicting Wireless Channel in multiple environments
• [N] Reliable low-latency networking: many radios, many paths
• [N] Hierarchical and distributed control of wireless networks
• [N] Build a clever Wi-Fi access point
• [ND] Bringing intelligence to Wireless Sensor Nodes
• [DN] Edge AI for a better wireless network
• [DN] One AI to rule them all (the wireless networks)
• [N] Connect: Ad-Hoc LoRa network in extremely lossy environments 
• [ND] Fixing the Wi-Fi in the future?: Predictive Forward Error Correction
• [ND] Finding the Truth: Probabilistic Graphical Models for cross-layer inference
• [SD] Securing your things: Find the anomaly in the IoT
• [SN] CommuniFi: Data transmission during device-free sensing of human activities
• [DN] VariFi: Variable WiFi data rates during device-free sensing
• [D] A Step towards Federated Learning
• [N] MaritimeManet in a Lab
• [N] Unleashing 5G: From Evolution to Implementation
• [N] Resource Management in IEEE 802.11ax based Networks for Spectrum Efficiency and QoS

Localization and Navigation

• [SD] Neural Inertial Navigation

Smart Mobility and Transport

• [SD] Smart Bikes: Trajectory Prediction with Onboard Sensors
• [SN] E-bell: Enabling bike to bike/car communication
• [N] Broadcast storm migration for V2V communication
• [N] Smart Bikes: Evaluating B2X wireless communication with realistic traffic simulator in urban scenarios [NEW]
• [SD] Smart Bikes: Who is Approaching Me? [NEW]
• [SD] Crowdsensing Road Quality using IMUs on the Bike [NEW]
• [SD] Cyclist Weight Inference [NEW]

IoT & Security

• [D,N] Comparative Study of Operating Systems for Docker Containers on IoT Devices
• [D,N] Hacking Traffic Lights
• [D] Empowering IoT with K3s: Optimizing Container Orchestration at the Edge
• [S,N] Virtualization for Swarms [NEW]

IT-security in mobile ad-hoc networks

• [S, N] Secure mobile ad-hoc routing in MaritimeManet

Construction Sites

• [D] Smartphone AR-Based Data Representation in Real-time for Construction Sites
• [D] Object Detection at Construction Sites
• [S,D] AI-driven Digital Twins for Construction Sites
• [D,S] Wearables at Construction Sites

Theses in Industry

The Pervasive Systems group collaborates very actively with many industry and research partners. Below is a list of interesting industry-lead research topics for the students interested in an experience in the industry sector.

• Several Projects on Embedded Machine-Learning with NXP AI-Team Eindhoven 
• [INTERNSHIP/THESIS] Functionality vs Usability, How to Balance in Embedded System? [NEW]