MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641057894 A) filed by Agni College Of Technology, Chennai, Tamil Nadu, on May 7, for 'zone-based real-time crowd detection and forecastin with yolov8 and machine learning.'
Inventor(s) include Raghuraman V; Monika S; and Srinidhi K.
The application for the patent was published on May 29, under issue no. 22/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to a method and system for real-time crowd monitoring, counting, data storage, and density forecasting using YOLOv8. The system comprises a plurality of video capturing devices configured to capture live video streams from designated locations. The captured video data is processed by a detection module employing YOLOv8 to identify and count individuals in real-time. The detected counts, along with corresponding timestamps and location information, are stored in a structured database for subsequent analysis. A forecasting module analyzes the stored historical and real-time data to predict future crowd density at specific locations and time intervals using statistical and machine learning techniques. The system further comprises a visualization module configured to generate graphical representations, including heatmaps, line charts, and trend graphs, of crowd distribution over time. An alert module is provided to generate notifications when crowd density exceeds predefined safety."
Disclaimer: Curated by HT Syndication.
