AI-Driven Facial Recognition System for Secure and Efficient Bike Starter Authentication Using Machine Learning

With the rise of smart technology, integrating facial recognition into vehicle security systems is becoming increasingly popular. This project aims to develop a Face Recognition-Based Bike Starter System to enhance bike security and prevent unauthorized access. The system employs a camera module to capture the rider’s face and compares it with a pre-registered database using AI-based facial recognition algorithms. If authentication is successful, the system triggers the bike’s ignition system; otherwise, access is denied. The proposed system uses OpenCV for image processing, a Raspberry Pi/Arduino for processing, and a relay module to control the ignition. Additionally, it can be enhanced with cloud storage for remote monitoring and mobile app integration for user convenience. The implementation of this technology significantly reduces the risk of theft compared to traditional key-based mechanisms. By leveraging advanced biometric authentication, this project introduces a secure, efficient, and user- friendly bike-starting mechanism. It represents a step forward in automotive security, blending AI, IoT, and embedded systems to provide a smart solution for modern-day /transportation challenges.