AI Traffic Monitoring Camera
Deploying advanced computer vision systems on edge hardware to optimize municipal traffic flows and vehicle counts in real-time.
The Challenge
Managing traffic congestion in growing urban zones requires high-accuracy vehicle tracking. Traditional induction loops are costly to install and maintain, prompting the need for non-intrusive, camera-based AI vehicle analysis.
Our Approach
We developed a lightweight computer vision pipeline using YOLO-based object detection, optimized to run on edge computing units (NVIDIA Jetson). This allowed real-time tracking of speed, category, and lane violations directly on-site.
The Solution
Our solution provides traffic management departments with a dashboard that displays live vehicle counts, traffic speed analysis, and immediate alerts for accidents or stalled vehicles.
Results & Impact
The system reduced average intersection queue delays by 18% during peak hours by enabling dynamic traffic signal controls based on actual vehicle queues.