MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641080382 A) filed by Dr. S Muthupandiyan; Dr. Riddhi Garg; Pradheeba P; Dr. V. Padma; Dr. G. Ambika; and Niaz Abdul Salam on June 30, 2026, for Emotion-Driven Stochastic Modeling Framework For Predicting Human Crowd Movement In Emergency Evacuations.
Inventors include Dr. S Muthupandiyan; Dr. Riddhi Garg; Pradheeba P; Dr. V. Padma; Dr. G. Ambika; and Niaz Abdul Salam.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The present invention discloses an Emotion-Driven Stochastic Modeling Framework for Predicting Human Crowd Movement in Emergency Evacuations that integrates emotional state assessment, stochastic decision-making, and agent-based simulation to accurately predict crowd behavior during emergency situations. The framework comprises an environmental data acquisition module, a crowd monitoring module, an emotional state estimation module, a stochastic behavior modeling engine, an agent-based crowd simulation module, a movement prediction module, and an evacuation analytics module. The emotional state estimation module determines parameters including fear, panic, anxiety, stress, and urgency levels based on environmental conditions and crowd dynamics. The stochastic behavior modeling engine utilizes these emotional parameters to generate probabilistic movement decisions, route selections, speed variations, and interaction responses. The agent-based simulation module models individuals as autonomous agents possessing unique emotional and behavioral characteristics. The movement prediction module forecasts crowd trajectories, congestion zones, bottleneck formations, evacuation routes, and evacuation completion times. The evacuation analytics module provides risk assessment, crowd distribution analysis, and emergency response recommendations. By incorporating emotional influences and uncertainty-aware behavioral modeling, the invention improves prediction accuracy, enhances evacuation planning, reduces crowd-related risks, and supports public safety management in airports, railway stations, shopping malls, stadiums, industrial facilities, educational institutions, and smart city infrastructures. The framework enables real-time and simulation-based emergency evacuation analysis for effective disaster management and decision support.
Disclaimer: Curated by HT Syndication.
