DCU-Final-Year-Projects-Booklet-2025

116 252. Connected Autonomous Surveillance Robot (CASR) The goal of this project is to design, build, and test a connected home surveillance robot. The robot autonomously navigates indoors, monitors for anomalies that may indicate a security threat, and notifies the user of any issues while capturing a video recording. The robot features a 3D-printed body, a Raspberry Pi 4, a differential drive using two DCmotors, a 2D LiDAR for mapping, and a camera for object detection. ROS 2 serves as the middleware, facilitating seamless hardware-software integration. The project encompasses CAD, 3D printing, electronics, sensor integration and fusion, SLAM (Simultaneous Localisation andMapping), and computer vision. A key focus is the fusion of 2D LiDAR data with camera data to enhance functionality. Student Programme Mechatronic Engineering (Year 5) Project Area 3-DModelling, Computer Vision, Control Systems, Embedded Systems, Mechatronic Systems, RaspberryPi, Robotics, Sensor Data, Software Development Project Technology C/C++, Digital Signal Processing, Python, Solidworks, ROS 2 Student Name(s) Fionn ÓMuirí Email fionn.omuiri2@mail.dcu.ie Supervisor Prof DerekMolloy 253. Kick-DrumPedal VelocityMeasurement This project investigates how an electronic kick drum is actuated, and improves upon it, by using a combination of rotational and distance sensors. Electronic drum kits are well-developed instruments and play a huge role in music. Traditionally, they are actuated by piezo-electric sensors recording the impact on the drum head. In this project, the actuation is recorded by angle sensors measuring the acceleration of the beater. This allows the impact material to be tuned to the feel of the drummer instead of being designed around the piezo-electric sensor. Student Programme Mechanical andManufacturing Engineering (Year 4) Project Area Sensor Data Project Technology Excel/VB Student Name(s) Cormac Hickey Email cormac.hickey38@mail.dcu.ie Supervisor Dr Alan Kennedy 254. DiaPi: Raspberry Pi Diabetes HealthMonitor DiaPi aims to offer a proactive approach to health management by providing a health monitoring system designed to help users manage their health through data collection and analysis. Utilising a Raspberry Pi, the system integrates sensors such as the DS18B20 temperature sensor and theMAX30100 pulse oximeter tomeasure vital signs, including heart rate, blood oxygen levels, and body temperature. Data is processed and stored in a normalised PostgreSQL database and visualised graphically via a web interface built with Django and React. The system features advanced data analysis andmachine learning capabilities to detect anomalies and provide predictive insights into health trends. Student Programme Computer Science Project Area Artificial Intelligence, Data Analytics, Databases, Internet of Things, RaspberryPi, Sensor Data, Sensor Technology, Speech Recognition, Web Application Project Technology CSS, HTML5, JavaScript, Matlab, Python, SQL, React.js, Machine Learning Student Name(s) Loone Univer  |  Ella Doyle Email loone.univer2@mail.dcu.ie   |  ella.doyle62@mail.dcu.ie Supervisor Mr Renaat Verbruggen