Abstract
Large crowd management presents a significant challenge to organizers and for the success of the event and to achieve the set objectives. One of the biggest events and with largest crowd in the world is the Muslim pilgrimage to Mecca that happens every year and lasts for five years. The event hosts over two million people from over 80 countries across the world with men, women, and children of various age groups and many languages. One of the challenges that faces the authorities in Saudi Arabia is that many of the pilgrims become astray during the event due to the relative complexity of the rituals mainly mountainous landscape and the language barrier. This result in them being unable to perform the required rituals on the prescribed time(s) with the possibility to invalidate the whole pilgrimage and jeopardize their once-in-a-life journey. Last year over 20,000 pilgrims went astray during the pilgrimage season. In this paper we present a tracking algorithm to help track, alarm, and report astray pilgrims. The algorithm is implemented on a server that contains pilgrims' data such as geolocations, time stamp and personal information such as name, age, gender, and nationality. Each pilgrim is equipped with a wearable device to report the geolocations and the timestamp to the centralized server. Pilgrims are organized in groups of 20 persons at maximum. By identifying the distance of the pilgrim to its group's centroid and whether or not the pilgrim's geolocation is where it is supposed to be according to the pilgrimage schedule, the algorithm determines if the pilgrim is astray or on a verge of becoming astray. Algorithm complexity analysis is performed. For better performance and shorter real-time time to determine the pilgrim's status, the algorithm employs an in-memory data structure. The analysis showed that the time complexity is O(n). The algorithm has also been tested using simulation runs based on synthesized data that is randomly generated within a specified geographical zone and according to the pilgrimage plan. The simulation results showed good agreement with the analytical performance analysis.