MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641061183 A) filed by Salem College Of Engineering And Technology on May 14, 2026, for Smart Traffic Flow Prediction Using Deep Learning And Real Time Data.
Inventors include M. Nithya; Rithik T; Sandhiya M; Santhosh S; Santhosh Kumaran T; Siranjeevi S; Sumithra M; and Thamaraiselvan M.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: A smart traffic flow prediction system usmg deep learning improves urban mobility management. The system collects real-time traffic data from cameras, sensors, and connected devices. Historical traffic information is also stored for analysis. Deep learning models process large volumes of traffic data. The system identifies patterns related to congestion and peak hours. Predictive algorithms estimate future traffic flow conditions. Authorities receive insights for better traffic signal planning. Real-time predictions help reduce congestion and travel delays. The system supports dynamic route optimization for commuters. Data visualization provides clear traffic trend analysis. Integration with intelligent transportation systems enhances coordination. Continuous learning improves prediction accuracy over time. The solution helps reduce fuel consumption and emissions. Scalable architecture supports deployment across multiple locations. Thi~ smart prediction system contributes to efficient and intelligent traffic management.
Disclaimer: Curated by HT Syndication.
