WorkerWatch AI

WorkerWatch AI – Bus Maintenance Worker Monitoring System

WorkerWatch AI is an intelligent computer vision platform developed to monitor maintenance workers inside bus maintenance facilities using existing surveillance camera infrastructure. The system applies advanced AI and deep learning models to detect, identify, and track workers in real time while improving workplace safety and operational awareness.

The platform continuously analyzes live video streams to monitor worker movement, presence, and operational activities. AI-powered analytics automatically detect abnormal situations and safety-related incidents, generating immediate alerts that enable rapid response and improve facility management.

Key Features

• Real-time worker detection and tracking.
• AI-powered monitoring using existing CCTV infrastructure.
• Continuous monitoring of maintenance activities.
• Detection of abnormal events and safety incidents.
• Instant notifications and automated alerts.
• High-accuracy computer vision and deep learning models.
• Centralized monitoring and operational analytics.
• Scalable deployment across maintenance facilities.

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, CCTV integration, real-time analytics implementation, performance optimization, testing, validation, and deployment. I designed and optimized the solution to deliver accurate worker monitoring while improving workplace safety and operational efficiency.

Technologies

Python, OpenCV, PyTorch, Deep Learning, Computer Vision, AI Video Analytics, CCTV Integration, Real-Time Monitoring, Image Processing, Artificial Intelligence.