TrafScan is a high-resolution vehicle detection camera system that utilizes machine learning-based computer vision algorithms. it effectively detects and monitors both moving and stationary vehicles at traffic signals, providing detailed verification of vehicle presence, counting, and classification into various categories.
Intelligent vehicle detector and counting system for intersectional traffic control. Capable of working in a heterogeneous vehicle type environment (e.g. cars, bikes, etc.), it detects stationary and in-motion vehicles using a live camera and state-of-the-art software algorithms. It helps to understand traffic density and queue length based on vehicle count and zone occupancy information, to reduce vehicle stoppage time, resulting in a smoother flow of vehicles and better junction traffic flow management.
Real-Time Vehicle Detection and Counting: Utilizes AI/ML algorithms to detect stationary and moving vehicles, providing accurate vehicle counts and occupancy data.
Traffic Flow Monitoring: Analyzes traffic density and queue lengths to optimize traffic signal timings, reducing stoppage time and improving junction traffic flow.
High-Resolution Imaging: Equipped with highresolution cameras to ensure precise detection and classification of various vehicle types, including cars, bikes, and heavy vehicles.
Integration Capabilities: Seamlessly integrates with third-party systems like traffic controllers to dynamically adjust traffic lights based on real-time data.
Red Light Violation Detection: Can function as an overview camera for detecting red light violations, enhancing traffic law enforcement.
Easy Installation and Maintenance: Designed for straightforward deployment and minimal maintenance, making it suitable for various urban traffic scenarios.
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