Title: SAHAYATA Framework for Crowd Management at Pilgrimage Sites


Authors: Namit Rathi, Prof. Nisha Rathi


Published in: Volume 3 Issue 1 Jan June 2026, Page No. 1-6


DOI: 10.63844/IJAITR.v3.i1.2026.1-6 cite


Keywords: Crowd management, IoT, pre-registration, stampede prevention, pilgrimage safety, predictive analytics


Abstract: Pilgrimage destinations, such as Kedarnath and Amarnath, experience severe overcrowding during peak seasons. It leads to safety concerns and operational challenges. Traditional crowd control methods react to problems after they occur rather than preventing them. This paper presents SAHAYATA (Smart Assistance & Safety System), a pre-registration and journey planning framework. The proposed system is based on predictive analytics, IoT-enabled identification, and dynamic allocation of slots. The system includes advance registration portals, QR-coded wristbands with LoRa communication, and real-time dashboards for authorities. Analysis of recent Indian stampedes, including Hathras (2024, 121 deaths) and Maha Kumbh (2025, 30 deaths), shows the critical need for proactive systems. SAHAYATA transforms reactive crowd management into data-driven governance through predictive crowd distribution, structured evacuation planning, and optimized resource deployment. Simulation studies and theoretical analysis point out the potential improvements in prediction accuracy, queue management, and emergency response capabilities compared to traditional systems.


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