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Introduction
WatchDocks is a smart surveillance system designed to tackle the pervasive issue of bike theft. Born from the shared frustration of losing bikes on campus, it combines real-time computer vision with instant alerts to protect cyclists' property.
Project Overview
WatchDocks uses a camera system powered by computer vision to monitor bike racks. It detects suspicious behavior—such as lock tampering or loitering—and triggers a two-pronged response: a loud siren to deter the thief and an immediate notification to the bike owner's phone.
Demo Video
Key Features
- ▶Real-time Theft Detection: Uses YOLOv8 and computer vision to identify suspicious activities like lock cutting or tampering.
- ▶Instant Alerts: Sends immediate notifications to the owner's mobile device via a React Native app (or web dashboard).
- ▶Active Deterrence: Triggers a loud siren when theft is detected to scare off perpetrators.
- ▶Context-Aware Analysis: Leverages the Gemini API to analyze activity patterns and generate context-aware warnings.
- ▶Secure Verification: Integrates Auth0 for secure user authentication and role-based access control.
How It Works
- ▶Monitoring: Cameras feed video to a Flask backend.
- ▶Detection: The system runs YOLOv8 models trained on RoboFlow to detect theft behaviors.
- ▶Alerting: If suspicious activity is confirmed, the system triggers a siren and sends an alert to the MongoDB database.
- ▶Notification: The React frontend polls for alerts and notifies the user.
- ▶Verification: Users can verify their identity to dismiss false alarms.
Technology Stack
- ▶Frontend: React.js, Tailwind CSS
- ▶Backend: Flask (Python)
- ▶AI/ML: YOLOv8, RoboFlow, Gemini API
- ▶Database: MongoDB
- ▶Authentication: Auth0
Challenges & Learnings
One of the main challenges was reducing false positives in motion detection—distinguishing between a student unlocking their bike and a thief tampering with a lock. We fine-tuned sensitivity thresholds and applied filtering logic to improve accuracy. We also learned the importance of low-latency processing for real-time security systems.