Autonomous multi-agent systems for pilgrim mobility and emergency response

Mass gatherings such as the Hajj pilgrimage and Kumbh Mela attract millions of participants, presenting unique challenges in crowd management, mobility coordination, and emergency response. Traditional systems often struggle with the scale, unpredictability, and real-time decision-making demands of such events. This article proposes the use of autonomous multi-agent systems (MAS) to address these challenges through decentralized, intelligent coordination among agents equipped with sensing, communication, and decision-making capabilities. Drawing upon a wide body of recent research in agent-based modeling, GIS integration, real-time evacuation management, and UAV autonomy, the study develops a conceptual MAS framework tailored for pilgrim mobility and emergency intervention. The framework is validated through simulation studies modeling crowd behaviors and agent responsiveness during hypothetical crises. Results demonstrate significant improvements in evacuation efficiency, congestion mitigation, and hazard avoidance when compared to centralized systems. Furthermore, the integration of real-time data analytics and autonomic computing enhances the adaptability and responsiveness of the system. This research contributes to the growing body of literature on AI-driven urban safety and offers practical implications for planners and policymakers managing high-density religious events in complex environments.