MetroCount AI

AI Metro Passenger Counting System (AMPCS)

AI Metro Passenger Counting System (AMPCS) is an intelligent computer vision platform developed to automatically detect, track, and count passengers across metro stations and train carriages in real time. The system utilizes AI-powered video analytics to generate accurate passenger statistics, occupancy levels, and movement insights that support smart transportation operations.

Designed for high-density public transportation environments, the solution processes live camera streams using advanced deep learning models capable of maintaining high counting accuracy under varying lighting conditions, station layouts, and heavy passenger traffic. The platform integrates with existing surveillance infrastructure to provide continuous monitoring and operational intelligence.

Key Features

• Real-time passenger detection, tracking, and counting.
• AI-powered computer vision and deep learning analytics.
• Accurate performance in crowded and complex environments.
• Occupancy monitoring for stations and train carriages.
• Live dashboards, analytics, and automated reporting.
• Integration with existing camera and sensor infrastructure.
• Scalable architecture for large transportation networks.
• Operational insights for planning and resource optimization.

My Role

I independently led the project from concept to deployment. My responsibilities included system architecture, AI model development, computer vision algorithm design, software engineering, infrastructure integration, performance optimization, testing, validation, documentation, and deployment. I optimized the solution to deliver reliable real-time passenger counting and analytics across high-volume metro environments.

Technologies

Python, OpenCV, TensorFlow, Deep Learning, Computer Vision, AI Video Analytics, IoT Integration, Pandas, Data Visualization, Cloud Computing, Real-Time Monitoring.