MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541122897 A) filed by Vellore Institute Of Technology, Vellore, Tamil Nadu, on Dec. 5, 2025, for 'real-time traffic flow prediction using spatiotemporal graph neural networks.'
Inventor(s) include Dr. Dhivyaa C R; Ms. Pramiti Shekhar Singh; and Mr. Surya Singha.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "The present disclosure provides a real-time traffic flow prediction system including a data acquisition module configured to collect traffic data from monitoring sources, a graph construction module configured to represent a traffic network as a graph structure wherein nodes correspond to monitoring locations and edges represent road segments, a spatiotemporal graph convolutional network module having spatial graph convolution layers configured to capture spatial dependencies between road segments and temporal convolution layers configured to model sequential traffic patterns, a real-time data processing module configured to receive streaming traffic data and update predictions dynamically, and a prediction output module configured to generate real-time traffic flow forecasts. The system processes traffic data through the spatiotemporal graph convolutional network to capture both spatial relationships and temporal evolution patterns, enabling accurate prediction of traffic conditions across urban transportation networks."
Disclaimer: Curated by HT Syndication.
