# Improving Response Time for Crowd Management in Hajj
## 1 Introduction  
Hajj is an annual religious event where millions of pilgrims from all over the world gather to perform certain ritual, which include mobility from one site to another. With this massive gathering of people, crowd management is a significant challenge to ensure safety and security for pilgrims during their movement. During Hajj, the crowd might walk for long distances between different sites, extending the risk zones and increasing the challenge of providing good crowd management. Figure 0(a) shows a crowded street full of pilgrims in one of the Hajj sites called Mina. Figure 0(b) shows the whole Mina site and most of its interconnected streets and pathways full of crowds. Hajj organizing authorities have deployed more than 4000 fixed surveillance cameras in different sites to monitor crowd safety. Figure 0(c) shows a control room receiving feeds  
Figure 1: Crowd Movement in Hajj (**a**) A Crowded Street During Hajj, (**b**) Mina Valley During Hajj, (**c**) A Control Room for Crowd Management. from various crowd-monitoring cameras. Despite its massive and wide deployment, fixed cameras have a limited view and limited alleviation. They do not cover large geographical areas without the use of complicated image merging and stitching technology. Moreover, fixed cameras lack a bird's-eye view, which is required for most crowd flow detection. Therefore, given the vast area that required coverage in the case of Hajj, image data from fixed cameras are insufficient for crowd-flow detection applications. The utilization of Unmanned Ariel Vehicles (UAV) or drones is becoming part of our daily life, especially in critical missions like search and rescue, surveillance, reconnaissance, and emergency response. In crowded situations, drone utilization is becoming increasingly interesting in the discovery of earlier signs of a stampede, congestion, and other crowd problems. Real-time images and videos taken by drones will have a wider field of view, cover huge areas, have zero obstruction in open areas, and have an adjustable alleviation view. In [1], the author provided a management framework for crowd events. They suggested using technologies to collect the pilgrims' data in Hajj, and later enhance security measures and crowd management. Most civilian applications that use UAVs and drones are offline or not time-critical. With mission-critical applications that require real-time imagery feed, capable communication modules should be provided with UAV to transmit real-time feed images. Finally, if the images captured by the UAVs are transmitted to the base station using typical FANET communication protocols, the FANET applications must wait for the entire image to be received before it can process the image. Image-processing applications require very large amounts of data to be exchanged between the UAV and base-station. In traditional wireless sensor networks that sense light, humidity, pressure, etc., the traffic generated by a sensing node is limited to the scalar data. In most cases, the memory size required to store and send is 16-bits per reading. On the other hand, image data are in kilobytes or even megabytes. For example, a raw Red-Green-Blue (RGB) image of 128 \(\times\) 128 pixels with 24-bits per pixel (8 bits per color) will be of 128 \(\times\) 128 \(\times\) 24 = 393,216 bits (approximately 48 kilobytes). These are magnitudes larger than traditional sensor data. Although image compression reduces the size of data to be transmitted, it is still not enough. [PERSON] et al. [2] presented a comprehensive survey about the FANET. The author discussed the design issues of FANET. These issues are: Node Mobility, Mobility Models, Node Density, Topology Changes, Radio Propagation Model, Power Consumption and Refueling, and Localization. The networking protocols for FANET are also discussed in detail, such as Static, Proactive, Reactive, Hybrid, and Geographical and Position-based protocols. The author also highlighted some of the research areas of FANET. One of the applications is disaster and crowd management.