MUMBAI, India, March 13 -- Intellectual Property India has published a patent application (202631014093 A) filed by C. V. Raman Global University, Bhubaneswar, Orissa, on Feb. 9, for 'vision driven adaptive traffic signal system for smart city.'

Inventor(s) include Brijesh Kumar Mohanty; Shruti Sharma; Chinmay Chatterjee; Harsh Raj; Ayushman Mishra; Sneha Srivastav; and Smita Rani Parija.

The application for the patent was published on March 13, under issue no. 11/2026.

According to the abstract released by the Intellectual Property India: "The present invention relates to an intelligent traffic management system, specifically a visiondriven adaptive traffic signal control system designed for smart cities. This innovation addresses critical urban challenges including traffic congestion, excessive vehicle idle time, environmental pollution, and delayed emergency response times. The system integrates computer vision technology, artificial intelligence, Internet of Things (IoT) sensors, and machine learning algorithms to create a real-time, self-optimizing traffic control infrastructure. Unlike conventional fixed-timing traffic signals, the proposed system dynamically analyzes real-time traffic flow using video feed analysis, vehicle detection, and congestion prediction to optimize signal timings for each intersection independently. The system further incorporates emergency vehicle detection capabilities, allowing automatic prioritization of ambulances, fire trucks, and police vehicles to ensure rapid emergency response. By leveraging renewable solar energy for power, the system demonstrates environmental sustainability while reducing operational costs. The AI-driven predictive analytics component learns from historical patterns and current conditions to anticipate traffic bottlenecks before they occur, enabling proactive signal adjustments. Comprehensive field deployments at multiple urban intersections have demonstrated significant improvements in traffic flow efficiency, reduced vehicle emissions, lower fuel consumption, and faster emergency response times. The system is deployable across diverse urban infrastructures and is scalable for city-wide implementation, making it an essential component of next-generation smart city initiatives globally."

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