Vertex Technologies LLC
Leading AI solutions provider transforming businesses through innovation.
Leading AI solutions provider transforming businesses through innovation.
The Traffic Video Analytics System is a real-time computer vision solution designed to enhance urban traffic management and toll operations. It processes live video streams from multiple cameras to detect vehicles, classify them into predefined categories, track their movement, count in/out flow, and perform automatic number plate recognition (ANPR). The system supports smart city infrastructure by enabling authorities to analyze traffic behavior, identify repeated vehicles, and optimize operations accordingly.
Key challenges included maintaining object tracking consistency in crowded traffic conditions, achieving high OCR accuracy in varying lighting conditions for number plate recognition, and synchronizing real-time analytics across multiple camera streams. Integrating multiple modules into a smooth, fast pipeline while handling high-resolution feeds also required careful resource management.
The system utilized YOLOv8 for its high-performance object detection capabilities and Bot-Track for efficient object tracking. PaddleOCR was integrated for robust ANPR handling Indian number plate formats. Real-time boundary-based counting logic was implemented using OpenCV. MongoDB was chosen for its flexibility in storing and querying vehicle metadata. Docker was used to containerize the complete pipeline for scalable deployment.
The project enabled accurate real-time vehicle analytics in complex urban environments, helping reduce congestion through improved signal control and supporting toll automation with ANPR. Authorities gained actionable insights from the generated data, including peak traffic times and frequent routes. The modular pipeline design ensures easy adaptation for new cities or highway deployments.
