DCU-Final-Year-Projects-Booklet-2025

63 93. Development of an Electrochemical Sensing Platform for Biosensing Applications This project focuses on the development and validation of a novel electrochemical sensing platform that integrates screen-printed electrodes (SPEs) onto a centrifugal system. The primary objective is to optimise the fabrication, placement, and electrochemical performance of SPEs, ensuring robustness, repeatability, and effective analyte detection. The integration of SPEs with a centrifugal platform presents a unique approach to scalable and automated biosensing. The design supports efficient fluid handling and analyte detection, laying the groundwork for advanced diagnostic and analytical tools in point-of-care and research settings. Student Programme Biomedical Engineering (Year 5) Project Area Biomedical Engineering, Sensor Technology Project Technology Excel/VB, Solidworks, microfluidics Student Name(s) Timofei Cotorobai Email timofei.cotorobai2@mail.dcu.ie Supervisor Dr Éadaoin Carthy 94. Feasibility of Using Industrial Computers for Use in Industrial Internet of Things (IIoT) Applications This project investigates the feasibility of using industrial computers in Industrial Internet of Things (IIoT) applications, focusing on their ability to capture, process, and transmit data to cloud-based platforms for real-time monitoring and analysis. The study, conducted in collaboration with Consynsys Technologies, evaluates Procaaso, a cloud platformdesigned for IIoT workflows, as a central component of the solution. The project covers the implementation process, including hardware configuration, deployment of the Extremity Nervous System (ENS) software, and integration with Procaaso for secure data transmission and visualisation. Student Programme Mechanical andManufacturing Engineering (Year 4) Project Area Automation, Cloud Computing, Control Systems, Databases, Educational, Internet of Things, Network Applications, Sensor Data, Sensor Technology Project Technology Docker, Python, REST Student Name(s) Tamunoboma Emmanuel Karibiye Email tamunoboma.karibiye2@mail.dcu.ie Supervisor Dr Nigel Kent 95. Optimal Control of a Thermal Energy Storage System to Improve the Energy Flexibility and Efficiency in Buildings The industrial sector consumes about a third of global energy, with significant electricity use for air- conditioning and refrigeration. These systems often peak during the day, causing high energy costs and strain on electricity infrastructure. This project through the use of Python in Anaconda aims to optimise the use of thermal energy storage and solar PV to reduce industrial energy costs and peak grid load, using techniques likeMixed Integer Nonlinear Programming (MINLP) or Metaheuristic optimisation like Genetic algorithm (GA) and Particle SwarmOptimization (PSO) among various other optimisation methods. Student Programme Mechanical and Sustainability Engineering (Year 5) Project Area Artificial Intelligence, Control Systems, Energy Conservation, Renewable Energy Technology, Simulation, Statistical Analysis, Thermodynamics, Optimisation Project Technology Python Student Name(s) Owen Kealey Email owen.kealey2@mail.dcu.ie Supervisor Dr Mohammad Saffari