Tracking and Analysis of Pilgrims' Movement Throughout Umrah and Hajj Applying Artificial Intelligence and Machine Learning

The lack of adequate mob safety supervision frequently results in human injuries and deaths involving in activities like entertainment, religious or political gatherings of public. In the case of a large-scale mob, a minor calamity can set off a stampede. In spite of the current advancements in artificial intelligence (AI) techniques and machine learning (ML) procedures, this is pretty possible detection to predict the movement of mobs to prevent possible detection disasters, even though numerous intellectual video investigation tools can detect and identify objects. POI searching is an intelligent mob tracking podium that uses mobility characterization and analytics. POI searching has been designed to assist mobile mob event safety management by forecasting and preventing future calamities using real-time info-mob-data classification and its analysis. Current video surveillance methods cannot effectively monitor mob gatherings in large open spaces because they lack scalability. Our approach can improve mob safety management by successfully incorporating mob analysis technique we have proposed. We focus on the identity, speed, and direction detection issues among various mob motion characteristics for the mobile group. Afterwards, we use these group semantics to track the for our POI searching tests, we conducted them in an actual mob event and a lab setting. Researchers found that mob searching can recognize mobile mob characteristics in actual time, which suggests that it can be used to help prevent potentially dangerous situations caused by a large mob's movement.