Traffic surveillance during Hajj season is a crucial consideration in making decisions and ultimately helping to run the business effectively. Usually, large numbers of people need to be handled for transportation and traffic control, such as thousands of buses and vehicles. Yet there is no reliable, real-time information on the Hajj movements needed for measurement, benchmarking, and continual improvement but it is a huge obstacle to efficient management. Such a challenge is addressed in this analysis by developing an API-based system of collecting and analyzing traffic information for real-time use. The system generates hajj route files which contain longitude and latitude-coding geospatial points. These files are then deposited on a web page that displays traffic statistics from the API for each station on each route at defined times. The collected data is then deposited into a series of databases to be used for statistical and analytic purposes, such as estimates of delays and congestion-level estimates. The proposed system provides solid and adaptive real-time analytics that enable better transportation decision making, user experience, and more efficient and safer transport management. The collected data could also be used to alert drivers to estimated journey times to holy sites, and the long-term study helps identify bottlenecks and improve road network design. Overall, this approach helps to develop intelligent decision support systems for sustainable, data-driven traffic management during the Hajj season.

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