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Enhancing Pilgrim Monitoring and Safety using Multi-Agent Systems and Artificial Intelligence

by Ayman M. Mansour
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 76
Year of Publication: 2026
Authors: Ayman M. Mansour
10.5120/ijca2026926308

Ayman M. Mansour . Enhancing Pilgrim Monitoring and Safety using Multi-Agent Systems and Artificial Intelligence. International Journal of Computer Applications. 187, 76 ( Jan 2026), 39-45. DOI=10.5120/ijca2026926308

@article{ 10.5120/ijca2026926308,
author = { Ayman M. Mansour },
title = { Enhancing Pilgrim Monitoring and Safety using Multi-Agent Systems and Artificial Intelligence },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2026 },
volume = { 187 },
number = { 76 },
month = { Jan },
year = { 2026 },
issn = { 0975-8887 },
pages = { 39-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number76/enhancing-pilgrim-monitoring-and-safety-using-multi-agent-systems-and-artificial-intelligence/ },
doi = { 10.5120/ijca2026926308 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2026-01-20T22:56:38.135479+05:30
%A Ayman M. Mansour
%T Enhancing Pilgrim Monitoring and Safety using Multi-Agent Systems and Artificial Intelligence
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 76
%P 39-45
%D 2026
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Every year, millions of Muslims gather in Saudi Arabia to perform Hajj, presenting immense challenges in health, safety, and crowd management. Recent incidents, including fatalities from extreme heat and overcrowding, highlight the urgent need for intelligent, responsive systems. This study proposes a comprehensive multi-agent system (MAS) integrated with artificial intelligence (AI) to enhance the safety and well-being of pilgrims during Hajj. Each agent in the system is assigned a specialized role, ranging from health monitoring and crowd control to communication, decision-making, and emergency response. The methodology leverages wearable sensors, environmental data, and predictive analytics to detect risks such as stampedes, health emergencies, and heat stress, enabling real-time, coordinated interventions. The system facilitates seamless communication between agents through an electronic platform, ensuring rapid response and informed decision-making. Additionally, this approach is scalable and adaptable to other large-scale events, such as the FIFA World Cup, and has potential applications in public health monitoring, environmental surveillance, and disaster management. By harnessing advanced technologies, this work aims to reduce fatalities, improve safety, and optimize the overall Hajj experience.

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Index Terms

Computer Science
Information Sciences

Keywords

Hajj safety; multi-agent system; Artificial intelligence; Crowd management; Health monitoring; Wearable sensors; Heat stress detection; Emergency response; Predictive analytics; Real-time decision-making; Large-scale events; Disaster management

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