DCU-Final-Year-Projects-Booklet-2025

68 108. Indoor Navigation Using BIMand Computer Vision This project focuses on interior navigation using computer vision and Building InformationModeling (BIM). It takes real-time images, analyses them to establish the user’s location, and gives optimal navigation within a building. The systemanalyses visual data tomatch the user’s location to a digital model using feature- matching techniques and/or a classificationmodel and determines the best route to a desired destination. With the integration of image recognition and pathfinding, the goal of this project is to improve accessibility and wayfinding in complicated interior spaces for both building owners and building users. Student Programme Electronic and Computer Engineering (Year 4) Project Area Artificial Intelligence, Augmented Reality, Computer Vision, Image/Video Processing, Software Development, Human-computer Interaction Project Technology Python, Machine Learning Student Name(s) TomDowdall Email tom.dowdall2@mail.dcu.ie Supervisor Dr Ali Intizar 109. Enabling Edge Analytics for Vehicle Tracking and ParkingOccupancy Detection/Prediction This project focuses on developing a cutting-edge smart parking solution that leverages Internet of Things (IoT) devices and edge computing to enhance urban parking efficiency. The design consists of sophisticated algorithms involving image processing and AI learning techniques capable of analysing video feeds from cameras installed in parking areas to identify vacant spots in real-time. Importantly, the system is engineered to prioritise user privacy by processing data locally on the cameras, ensuring that no images or videos are transmitted to external servers. The programme will serve as a valuable tool for city planners and residents, facilitating smarter urban mobility solutions, making urban parking more efficient, user-friendly, and sustainable compared with current solutions. Student Programme Electronic and Computer Engineering (Year 4) Project Area Artificial Intelligence, Computer Vision, Image/Video Processing, Internet of Things, Security, Software Development, Traffic Simulators Project Technology Python, Machine Learning Student Name(s) LiamKelly Email liam.kelly242@mail.dcu.ie Supervisor Dr Ali Intizar 110. Evaluating the SEAI One-Stop-Shop Retrofitting Scheme’s Potential to Increase Retrofit Adoption AmongHouseholds in Ireland. This project evaluates the SEAI One-Stop-Shop (OSS) retrofitting scheme and its potential to increase uptake among Irish households. Using Design-Builder, energy models assess retrofit solutions to address key barriers such as high costs and disruption. Two scenarios are analysed: one prioritising affordability while achieving a B2 BER, and another focusing on minimising intrusiveness while maintaining efficiency. A cost-benefit analysis, including NPV assessment, determines the economic viability of each approach. Research and data-driven insights, alongside international OSSmodels, inform recommendations to enhanceOSS effectiveness, improve homeowner engagement, and support Ireland’s 2030 retrofit targets. Student Programme Mechanical and Sustainability Engineering (Year 5) Project Area 3-DModelling, Energy Conservation, Renewable Energy Technology Project Technology Design-Builder Student Name(s) PadraicMoylan Email padraic.moylan3@mail.dcu.ie Supervisor Dr Lorna Fitzsimons