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Project Overview:
The Smart Bike Automation System combines IoT and Edge AI to enhance bike security, convenience, and user experience. Utilizing the Arduino UNO R4 Wifi, this project offers seamless Bluetooth connectivity to automatically control the bike's power, a self-start feature, and intelligent location and locking functionalities via a mobile app. The system incorporates an ADXL345 sensor for movement detection and alarms, a PN532 NFC module for secure switching, and visual LED indicators. Edge AI analyzes sensor data for predictive maintenance and real-time anomaly detection, ensuring optimal performance and security.
Key Features:
1. Bluetooth Connectivity: Automatic bike on/off based on Bluetooth connection.
2. Mobile App Integration: Self-start, locate, and lock functionalities.
3. ADXL345 Sensor: Detects movement and triggers alarms.
4. PN532 NFC Module: Secure bike switching via NFC.
5. LED Indicators: Visual cues for bike status.
6. Edge AI Integration: Predictive maintenance and real-time anomaly detection.
Technical Implementation:
- Microcontroller: Arduino UNO R4 Wifi
- Sensors and Modules:ADXL345, PN532, Bluetooth module, GPS module
- Software: Arduino IDE, AI algorithms for edge processing
- Power Management: Efficient use of battery for extended functionality
Why This Project Should Be Selected:
This project exemplifies innovation in IoT and Edge AI by providing a comprehensive, intelligent solution for bike automation. It not only enhances security and usability but also demonstrates the practical application of advanced technologies in everyday life. The use of Arduino UNO R4 Wifi ensures reliability and ease of development, supported by a vast community. The project's focus on predictive maintenance and anomaly detection showcases forward-thinking, making it a standout entry in the competition.