학술논문

Integrative Technologies for Real-Time Crowd Management: A Case Study of the Hajj
Document Type
Conference
Source
2024 11th International Conference on Computing for Sustainable Global Development (INDIACom) Computing for Sustainable Global Development (INDIACom), 2024 11th International Conference on. :203-211 Feb, 2024
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
General Topics for Engineers
Geoscience
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Machine learning algorithms
Codes
Source coding
Bibliographies
Government
Process control
Machine learning
crowd management
privacy
security
artificial intelligence
Hajj
Language
Abstract
Crowd management is a very complex process, which requires the integration of many technologies together to create a reliable tool in crowd flow control. The historical events resulting from stampedes are the greatest evidence of the need for an effective solution. Relying on one method is not a reliable solution in such critical systems that require real-time response. The purpose of this research is to develop a smart framework that uses Artificial Intelligence (AI) and other technologies to control and manage crowds. The methodology involved conducting literature review and using a case study of Hajj event to develop a Python-based solution for running the framework. The findings shows that the framework is effective in crowd management, but it would be improved using advanced machine learning techniques. The proposed approach will help government agencies and other bodies to focus on adopting modern levels of technology in crowd management.