Smart Eye

Facilities with high vehicle turnover struggle with manual logging, leading to inefficiencies and data inaccuracies.

• Manual logging is error-prone and labor-intensive.
• Difficulty in tracking vehicle duration and occupancy in real-time.
• Congestion during peak hours due to slow manual checks.
• Lack of historical data for operational optimization.

We engineered a robust computer vision pipeline that automates the entire vehicle monitoring process.

• Real-time vehicle detection and robust tracking using ByteTrack.
• Automated license plate recognition and timestamp logging.
• Integration with a PyQt5 dashboard for live monitoring and alerts.
• Statistical reporting module for daily and monthly traffic analysis.