Eva Anton , Bryan Anton and Eric Feron , King Abdulla University of Science and Technology, Kingdom of Saudi Arabia

The Hajj pilgrimage, an annual Islamic ritual in Makkah, Saudi Arabia, attracts 2–3 million participants, presenting unparalleled crowd management challenges due to its spatial and temporal constraints, diverse demographics, and inherent safety risks. This article synthesizes insights from four seminal studies to assess how advanced technologies, ranging from crowd simulation models to artificial intelligence (AI), machine learning (ML) and a wide range of digital tools, can mitigate these challenges. Researchers propose a multi-layered framework that integrates predictive planning, real-time monitoring, and pilgrim-centric support systems to enhance safety, efficiency, and scalability. Findings highlight the transformative potential of these technologies while identifying critical gaps, such as scalability and real-world validation, that future research must address to ensure their efficacy during this massive gathering.

AI, Crowd Management, Hajj, CNN