Raspberry Pi–based cyber-physical system for e-bike monitoring over the internet

Toh, Erin Lih Xian (2025) Raspberry Pi–based cyber-physical system for e-bike monitoring over the internet. Final Year Project, UTAR.

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Abstract

This project addresses the growing problem of e-bike theft by developing a Raspberry Pi-based Cyber Physical System (CPS) for real-time monitoring and security. With e-bike theft rates significantly exceeding motor vehicle theft and recovery rates below 15%, innovative anti-theft technologies combining prevention and recovery capabilities are urgently needed. The system integrates facial recognition using the InsightFace framework, motion detection via MPU6050 sensors, and GPS tracking with the NEO-6M module. The Raspberry Pi 4 Model B coordinates sensor data through an event-driven architecture, enabling real-time threat assessment and immediate response activation. A Logitech C270 webcam provides biometric authentication, distinguishing between authorised and unauthorised users with a confidence-based assessment. MQTT communication protocols via EMQX broker ensure reliable data transmission to a cross-platform Flutter mobile application. The mobile interface provides comprehensive monitoring through facial recognition results, interactive GPS tracking with route visualisation, and system status monitoring. Security events automatically trigger GPS tracking activation and mobile notifications for immediate theft response. Testing in Kampar, Malaysia, demonstrated reliable performance with successful unknown face detection, automatic security response activation, and accurate location tracking. The system achieved effective integration of biometric authentication, motion sensing, and location tracking into a unified security platform, providing automated theft detection and asset recovery capabilities essential for ebike protection in urban environments.

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