# Improving Response Time for Crowd Management in Hajj
## 2 Related Work
The routing protocols can be classified into five major categories, including static routing, position-based routing, and Hierarchical routing, position-based routing, swarm-based routing, hierarchical routing, and topology-based routing. [PERSON] et al. [12] provide a review of the FANET communication perspective on wireless technologies, applications, challenges, and open research topics. Some of the applications they cited include monitoring, search and rescue. These applications require multimedia capture and transmission from drones. In addition to the challenges faced by FANETs, they also provide a list of available options for communication between the drones and base stations. The authors of [13] designed a FANET with a fleet of drones for monitoring rural areas that do not have Internet access. They argue that monitoring rural areas can be time-consuming, labor-intensive, and expensive due to the limited access and large distances to cover. They use drones to overcome these challenges. In their paper, they presented a FANET video monitoring platform by describing the architecture, the service chains used to realize the video delivery service, and an analytical model used to evaluate the computational load of the platform nodes to allow the network orchestrator to decide the backbone drones where the virtual functions will be run, and the relative resources to be allocated. [PERSON] et al. [14] also provide a similar solution. They argue that public ground networks do not provide sufficient coverage, which has resulted in the problematic backhaul of monitoring data from remote areas of interest. Because of the urgent demand for low-cost data collection in such areas, they propose a drone-enabled IoT relay system to provide high-speed data collection to support remote environmental monitoring. Their solution is based on 5 GHz and LoRa technology. They carried out numerous real-world experiments to validate the designed drone-enabled IoT relay the system's effectiveness and show its capability of high-speed data collection. [PERSON] et al. [15] suggest using drones for surveillance of violent individuals using ScatterNet Hybrid Deep Learning Network. Their system detects the violent individuals in real-time by processing the drone images in the cloud. [PERSON] et al. [16] talk about the collaboration of UAVs and unmanned ground vehicles (UVGs) in intelligence gathering, border surveillance, and crowd control. They propose a comprehensive planning and control framework based on a dynamic-data-driven, adaptive multi-scale simulation (DDDAMS). They discussed their solution and shared the results of their framework, algorithms, and testbed. [PERSON] et al. [17] discuss the estimation of crowd density from images captured from UAVs using corner detection and cluster analysis. They propose a testing procedure based on a feature from accelerated segment test (FAST) algorithms with a high level of correctness. Previously, [18], they proposed and tested a crowd monitoring system for pedestrians. They deployed a crowd monitoring technique using real-time images taken by UAVs. Captured images were analysed to calculate crowd density using image segmentation procedures. [PERSON] et al. [19] presented the UAV potential and IoT devices in crowd surveillance. They presented an IoT-based platform and developed a testbed for crowd surveillance. In crowd surveillance, the UAV can help provide safety to people, detect criminal activities, use facial recognition, and many other applications. In their crowd surveillance experimentation, they used a UAV equipped with a video camera, sensing devices and modems, and used an LTE network to connect with the base station. The primary purpose was to evaluate the energy consumption of UAVs during onboard processing and ground station processing. The UAV onboard video and image processing took a lot of time and energy. [PERSON] et al. [20] presented a geolocation-based routing protocol for FANETs. Their protocol supports multihop routing.