DCU-Final-Year-Projects-Booklet-2025

51 57. Moment – UnfilteredDating This project is an iOS dating application designed around authenticity by requiring users to take a daily unfiltered photo before accessingmatches. Each day, users receive a prompt to capture their current moment – granting themaccess to browse andmatch with others who have done the same. The system keeps a rolling history of each person’s last few daily photos alongside their profile information, allowing potential matches to see recent, genuine snapshots of daily life. Features include a tailoredmatching algorithmbased on people’s actual interests and pictures, real-time messaging, and an intuitively designed interface. Through combining daily photos with traditional dating app functionality, Moment creates an environment that bridges the gap between online personas and real-life. Student Programme Computer Science Project Area Image/Video Processing, Instant Messaging, Mobile App, Social Networking Project Technology Docker, Go, SQL, Swift, GraphQL, Machine Learning Student Name(s) Oisín Duggan  |  Alexander Petrash Email oisin.duggan5@mail.dcu.ie  |  alexander.petrash4@mail.dcu.ie Supervisor Dr JohnMcKenna 58. ISL Interpreter This project investigates the development of a system that translates Irish Sign Language (ISL) into text using computer vision andmachine learning. The system captures hand gestures through a webcam, processes them using OpenCV andMediaPipe, and classifies themwith a neural network trained on ISL gestures. The goal is to improve accessibility for the deaf community by providing a real-time, user-friendly translation tool. Challenges such as accurate gesture recognition, dataset collection, and model optimisation were addressed to enhance systemperformance. The final solution offers a reliable and efficient means of recognising ISL gestures demonstrating the potential of AI-driven sign language translation. Student Programme Electronic and Computer Engineering (Year 4) Project Area Artificial Intelligence, Computer Vision, Sensor Data, Software Development, Human-computer Interaction Project Technology Python, Machine Learning Student Name(s) Jack Brophy Email jack.brophy25@mail.dcu.ie Supervisor Dr Leah Ridgway 59. Safety Analysis onMicromobility Systems The project aimed to analyse the safety of micromobility systems for the purpose of route optimisation. A Kaggle dataset on traffic accidents was used and preprocessed to facilitate easier analysis. The cleaned dataset was then utilised tomake predictions by developing a visualised HTML heatmap, highlighting how accident-prone specific locations were. This involved converting geographic coordinates into OpenStreetMap identifiers. The processed data was subsequently used to identify optimal routes —both the safest and the shortest —between two points. Route optimisation was performed using an edge-based graph approach and the Dijkstra algorithm. Two randompoints were selected, the distance between themwas calculated, and the safety of the route was assessed. An HTML map was developed to visualise the routes and was compared with GoogleMaps to evaluate accuracy. Areas with high severity scores were identified and discussed, and conclusions were drawn based on the findings. Student Programme Electronic and Computer Engineering (Year 4) Project Area Data Analytics, Databases, PredictionModels Project Technology Python, Machine Learning Student Name(s) Ben Zikang Crane Email ben.crane2@mail.dcu.ie Supervisor Dr Mingming Liu