MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641107586 A) filed by Talari Ashok; Dr. Krishna Kumar; Adarsh Tiwari; Ms. Kajal Sharma; Adv. Gurudev Singh; and Prof. Dr. Ravuri Hema Krishna on September 07, 2026, for Smart Traffic Congestion Prediction System Using Iot Sensors And Machine Learning.
Inventors include Talari Ashok; Dr. Krishna Kumar; Adarsh Tiwari; Ms. Kajal Sharma; Adv. Gurudev Singh; and Prof. Dr. Ravuri Hema Krishna.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: A smart traffic congestion prediction system using internet-of-things sensors and machine learning is disclosed. A plurality of internet-of-things sensors, such as inductive, magnetic, radar, acoustic, or camera-based sensors, is disposed along a road network and senses traffic parameters, the vehicle count, speed, occupancy, and flow, transmitting the data over a communication network to a processing platform. The platform aggregates the sensed data with contextual data, comprising time, day, weather, and events. A machine learning module, comprising a recurrent, long short-term memory, convolutional, or graph neural network trained on historical traffic and contextual data, learns the spatiotemporal patterns by which congestion forms and predicts a traffic congestion at a location at a future time, before it occurs, with a lead time sufficient for anticipatory action, updating the prediction in real time. A traffic management module applies the predicted congestion to anticipatory actions, controlling traffic signals to regulate flow, routing or diverting traffic, and informing travellers, taken before the congestion forms so as to prevent or mitigate it, in place of the reactive management that responds only after congestion has formed.
Disclaimer: Curated by HT Syndication.
