Anti Theft Bike Lock

Smart. Secure. Theft-Proof. An advanced RFID-enabled bike lock with real-time motion detection, automated image capture, and app-based control to keep your bike safe from theft

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Inspiration

The idea for this project was born out of the increasing cases of bicycle theft. Many traditional bike locks can be broken or bypassed easily. We wanted to build a smart, technology-driven solution that enhances security and provides real-time theft detection.

What it does

  • RFID Authentication: Only registered users can unlock the bike by tapping their RFID tag.
  • Rack-Pinion Locking Mechanism: A servo motor moves the rack to lock/unlock the bike.
  • IMU-Based Theft Detection: If a sudden jerk or movement is detected, the system recognizes it as a theft attempt.
  • Real-Time Image Capture: On detecting suspicious activity, the onboard camera captures an image and sends it to the app.

How we built it

  • Hardware:

    • Arduino Uno for processing RFID and IMU data.
    • RFID sensor for user authentication.
    • Servo motor for controlling the locking mechanism.
    • IMU sensor to detect unauthorized movement.
    • Onboard camera to capture images when theft is detected.

  • Software:

    • React Native app to register users and control the lock.
    • Python Flask backend for processing requests and handling RFID authentication.
    • Docker-based architecture to manage all services.
    • WebSocket communication for real-time alerts.

Challenges we ran into

  • CORS issues while integrating the React Native app with the Python backend.
  • Synchronizing IMU data to accurately detect a theft attempt without false alarms.
  • Optimizing the RFID response time to ensure smooth unlocking.
  • Integrating camera capture to work seamlessly when a theft is detected.

Accomplishments that we're proud of

  • Successfully built a fully functional, smart bike lock.
  • Achieved real-time theft detection using IMU sensors.
  • Implemented secure RFID authentication with a robust database.
  • Integrated an onboard camera system that captures and sends images in case of theft.

What we learned

  • RFID authentication mechanics and how to integrate them with a mobile app.
  • IMU-based motion detection for security applications.
  • React Native and Flask integration for real-time IoT applications.
  • Dockerizing applications for easier deployment and service management.

What's next for Anti-Theft Bike Lock

  • GPS Tracking: Adding a GPS module to track the bike's location in case of theft.
  • Remote Locking via App: Enabling users to lock/unlock the bike remotely through the mobile app.
  • Cloud Storage for Images: Uploading captured images to a cloud service for better accessibility.
  • Alarm System: Integrating a buzzer that activates when unauthorized movement is detected.
  • AI-Based Threat Detection: Using machine learning to differentiate between normal movements and theft attempts.
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