DCU Expo 2024 - Final Year Projects

81 153. Novel Multilayer Micro-Channel FabricationMethod by Removal Inserts The primary aimof this project was to develop an innovative and cost-effective approach for micro- channel fabrication, specifically tailored for integration intomicrofluidic devices. This investigation focused on leveraging capillary action and degas-driven flowmechanisms to facilitate fluidmovement within the channels. To achieve this goal, various wire types were utilised in conjunction with 3D-printed resin structures to fabricate microchannels within a PDMS chip. This approach afforded flexibility in channel orientation and height, thereby enhancing the versatility of the microfluidic system. This method can be regarded as the first of its kind and could eliminate the need for microfluidic devices to be created on a layer-by-layer basis. Student Programme Biomedical Engineering (Year 5) Project Area 3-DModelling, AdvancedMaterial Engineering, Biomedical Engineering, Device Design, FluidMechanics Project Technology Solidworks, Microfluidics, ElegooMars 4 Resin Printer Student Name(s) LeahMacken Email leah.macken5@mail.dcu.ie Supervisor Dr Eadaoin Carthy 154. Train Track Fault Detection UsingMachine Learning This project investigates the application of onboard accelerometer data for detecting railway track faults. Utilising accelerometers mounted on an in-service train, it captures acceleration data across the X, Y, and Z axes, synchronised with GPS coordinates. Known track defects provide a baseline for analysis. Data is analysed using the K-means algorithm in Python, an unsupervised learningmethod that clusters data points to identify anomalies. By experimenting with various clusters, the project aims to optimise anomaly detection. The effectiveness of the K-means algorithm is validated by comparing its findings against the locations of known track defects, where it successfully identifies all defects, demonstrating its high potential as a valuable tool for railway maintenance. Student Programme Mechanical andManufacturing Engineering (Year 5) Project Area Data Analytics, Mechanical Design andManufacture, Sensor Data, Software Development, Machine Learning Project Technology Python, Machine Learning Student Name(s) AdamNashat Email adam.nashat2@mail.dcu.ie Supervisor Dr InamUl Ahad 155. NightStop NightStop is a web application targeting students interested in nightlife across Dublin, with plans to expand nationwide. Catering to part-time working students with budget constraints, it collaborates with drivers and passengers within Dublin, providing affordable and secure transportation to and from nightclubs. It provides a cheaper service through ride-sharing and a bidding system for drivers. NightStop also prioritises user safety, conducting background checks on drivers and passengers to foster a comfortable and secure environment. We also provide a booking system, making it convenient for users to secure a taxi before their night out, which will give them the comfort of knowing they have a way home. Student Programme Enterprise Computing Project Area Databases, Environmental Mapping, Mobile App, Web Application, Intell Transport System Project Technology CSS, HTML5, JavaScript, MySQL, Python, Django Student Name(s) James Kelly  |  Jack Byrne Email james.kelly258@mail.dcu.ie  |   jack.byrne267@mail.dcu.ie Supervisor Dr Michael Scriney