MUMBAI, India, Jan. 9 -- Intellectual Property India has published a patent application (202521109858 A) filed by Pankaj Kunekar; Vishwakarma Institute Of Technology; Ravishankar Bhaganagare; Ruchit Hande; Harsh Detroja; Hardik Desarda; Rutika Harde; Jayesh Hage; and Akash Harkar, Pune, Maharashtra, on Nov. 12, 2025, for 'adaptive iot-based smart traffic signal control system using real-time vehicle density analysis.'
Inventor(s) include Pankaj Kunekar; Vishwakarma Institute Technology; Ravishankar Bhaganagare; Ruchit Hande; Harsh Detroja; Hardik Desarda; Rutika Harde; Jayesh Hage; and Akash Harkar.
The application for the patent was published on Dec. 12, under issue no. 50/2025.
According to the abstract released by the Intellectual Property India: "The invention discloses a Smart Traffic Control System (STCS) for intelligent urban mobility. The system automatically regulates traffic-signal timings based on real-time vehicle density measured by sensors such as ultrasonic or infrared detectors. A microcontroller (Arduino UNO/MEGA) serves as the processing core, executing an adaptive algorithm in which green-light duration is computed from the base time and deviation of current density from the average. This dynamic control significantly reduces waiting periods, congestion, and fuel wastage compared with fixed-cycle signals. The STCS can operate as a stand-alone intersection controller or as part of a network of IoT-enabled nodes communicating with a cloud server. Through the cloud layer, aggregated data from multiple intersections undergo predictive analysis using machine-learning models, enabling proactive adjustments before congestion develops. Additional modules permit detection and prioritization of emergency vehicles via RFID, GPS, or acoustic sensors, while optional pedestrian interfaces ensure safe crossings. Simulation using Proteus 8.9 demonstrated 95-98 % detection accuracy and a 30 % reduction in average wait time. Because the hardware uses low-cost microcontrollers and sensors, the invention is economically viable for developing cities. Future extensions include integration with environmental sensors for pollution tracking and AI-based adaptive learning for large-scale smart-city ecosystems. The disclosed STCS thus provides a real-time, low-cost, scalable, and sustainable solution for managing urban traffic, improving road safety, and reducing environmental impact."
Disclaimer: Curated by HT Syndication.
