DCU-Final-Year-Projects-Booklet-2025

108 228. Comprehensive Lecture Capture Device This project aims to develop on an existing prototype for capturing lecture content froma whiteboard by addingmotion-tracked lecturer capture, audio capture and adding functionality to capture high-quality scans of blackboard content. The prototype is to be developed on a Raspberry Pi computer as a proof of concept for the systems and algorithms in use, as was the case for the previous prototype. The project scope also includes qualitative testing of the device under different conditions such as camera angle, distance, lighting conditions and level of chalk residue on the chalkboards in order to verify the effectiveness of the device. Student Programme Mechatronic Engineering (Year 4) Project Area Computer Vision, Device Design, Image/Video Processing, RaspberryPi Project Technology Python, Solidworks Student Name(s) Michael Marrinan Email michael.marrinan3@mail.dcu.ie Supervisor Dr Brendan Hayes 229. End of Life Cycle Assessment ofWind Turbines &Wind Turbine Blades This project investigates the end-of-life (EOL) processes for wind turbines, with a particular focus on the challenges associated with the disposal and recycling of wind turbine blades. Given the increasing adoption of wind energy, the disposal of wind turbine blades presents significant environmental and logistical challenges, as they are composed of materials that are difficult to recycle. The project reviews various disposal methods and aims to conduct a Life Cycle Assessment (LCA) to evaluate alternative approaches for blade disposal, using standard landfilling as a benchmark for comparison. The findings will contribute to identifyingmore sustainable practices in wind turbine EOL management, with the goal of improving the environmental performance of wind energy systems. Student Programme Mechanical and Sustainability Engineering (Year 5) Project Area Renewable Energy Technology, Life Cycle Assessment Project Technology SimaPro Student Name(s) Wojtek Sychowicz Email wojteksy@hotmail.com Supervisor Dr GregMcNamara 230. Aegis – Blockchain Enabled, Federated Learning Framework for Cyber Threat Detection This project develops Aegis, a decentralised cybersecurity framework that uses federated learning and blockchain technology to strengthen threat detection efforts across distributed networks. Aegis promotes trainingmachine learningmodels to analyse network traffic locally on nodes without sharing raw data. The framework aggregates model updates from individual nodes to refine a global threat detection model that is redistributed to the nodes to enhance all security systems globally. Aegis is tested in a simulated environment using virtual machines (VMs) to emulate distributed nodes and real-life network conditions. This project highlights the potential of machine learning to boost cybersecurity in modern, interconnected systems. Student Programme Computer Science Project Area Artificial Intelligence, Cloud Computing, Data Analytics, Distributed Systems, Network Applications, Security, Software Development, Web Application, Blockchain Technology Project Technology CSS, Docker, HTML5, JavaScript, MongoDB, Nodejs, Python, REST, React.js, Machine Learning Student Name(s) Bhargav Panicher  |  TeniolaMalomo Email bhargav.panicher2@mail.dcu.ie   |  teniola.malomo2@mail.dcu.ie Supervisor Mr RayWalshe