A systematic literature review of emergency communications assisted by unnamed aerial vehicles

Reliable communication systems are critical during emergency scenarios such as floods, earthquakes, fires, and hurricanes to ensure timely information exchange and minimize damage. However, traditional communication infrastructure is often severely compromised during such events. Unmanned Aerial Vehicles (UAVs) have emerged as a promising solution to deploy temporary communication networks in disaster-affected areas. Although several studies have proposed architectures and deployment strategies for UAV-assisted communication, and reviews have addressed their potential, comprehensive discussions on protocol configurations, architectural considerations, and deployment parameter optimization remain limited. This paper presents a systematic literature review covering the period from 2014 to 2024, focusing on the use of UAVs in emergency communication systems. The reviewed articles are classified into a structured taxonomy according to the emergency scenario, UAV role, communication architecture, and protocol layer. Additionally, common communication parameters optimized for deployment, such as coverage and throughput, and the optimization methods employed, including heuristic and artificial intelligence techniques, are identified. The findings reveal that UAVs are predominantly deployed as aerial base stations for large-scale dynamic disasters, with protocol development focusing mainly on the physical, data link, and network layers. However, the lack of standardized deployment guidelines and limited real-world experimentation highlight a significant research gap. This review underscores the need for benchmark methodologies to support the effective and comparable deployment of UAV-assisted emergency communication systems. • This review spans ten years of UAV use in emergency communication systems. • A classification of scenarios, architectures, and protocols is proposed. • UAVs mainly support physical, data link, and network communication layers. • Optimized deployment using AI and heuristics improves network performance. • Real-world validation and deployment guidelines are still lacking.