Undergraduate projects 2024
- Developing a lightweight counter-drone system using Software Defined Radios The protection of public spaces, tourist areas as well as large events against malicious drones has become a major concern within the European Union. The introduction of drones in the market, coupled with their diminishing costs and increasing capabilities has become a game-changing threat to the protection of citizens in public spaces. The aim is to design, develop and implement a lightweight, portable and scalable counterdrone system that extracts information (including position, and trajectory) of rogue drones, process that information to implement risk-assessment features.
- Cooperative Aerial Robots Inspection implementation in Python This project is dedicated to the development of collaborative path planning algorithms that will take into account emergency response application requirements (i.e., sensing precision and coverage). Specifically, the following novel capabilities will be developed: a) Cooperation (i.e., swarm) techniques, for object detection that will facilitate decision support and adaptive flight path re-planning b) Optimized multi-drone scheduling for perpetual operation in extended missions
- Autonomous drone landing on charging pad through an Android app implementation This project will implement an Android app for a DJI Mavic drone for autonomous (re)charging operations. Specifically, the following novel capabilities will be developed: a) Autonomous take-off and landing on charging pad b) Trajectory planning and collision avoidance
- Reinforcement Learning Implementation for Urban Air Mobility on Nvidia Jetson in Python Urban Air Mobility (UAM) is at the crossroads of intelligent transportation and unmanned aerial systems. In UAM, autonomous aerial vehicles (drones) are envisioned as means of transporting commuters/goods as opposed to traditional road vehicles. The introduction of UAM is expected to revolutionize the transport sector, and alleviate the congestion problem that significantly impacts the environment and the economy. Existing drone-simulators in Gazebo-ROS will be used to generate relevant datasets and Reinforcement Learning algorithms will be implemented in Python to training and evaluate fully autonomous and human-robot coordination systems. Interested students will also get the opportunity to evaluate their algorithms on state-of-the-art commercial off-the-self drones.
- Implementing an ActivityPub Web App for enhanced Public Health Data Management Systems The aim of this project is to implement the ActivityPub protocol into a web app for collecting and sharing public health data. By doing so, this app will be able to communicate with other apps on the federated network, enhancing the reach and utility of the public health data management system. The aim is to demonstrate that novel health data management systems can have real-time tracking and mapping of health data and in doing so enable public health officials to identify early on incidents such as local hot spots of public health nature.
- Developing a Named-Data-Networking Android App for next generation Mobile Internet Access NDN changes the way data is retrieved in a network, potentially leading to more efficient data retrieval and lower latency. This can significantly improve the user experience, especially in mobile environments where network conditions can vary. In addition, security is integrated at the data level, not at the network level. This means that data can be secured regardless of where it is coming from, enhancing the security of mobile internet access. Hence, NDN is particularly well-suited for Internet of Things (IoT) applications and thus this thesis aims to develop an NDN Android app could seamlessly integrate with IoT devices, providing a unified platform for managing and accessing various IoT devices.
- Enhancing Contact Tracing Android apps with anonymised interaction features ,
CovTracer-EN: The official contact tracing mobile app of the Republic of Cyprus
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Developing a Web-based online map for Wireless Networking Signal Quality Monitoring This project will build upon our existing prototype web-app developed in Django to enable new features for monitoring the wireless spectrum and specifically its signal quality, identify out-of-distribution (OOD) events and report them.