## 4 Use Cases and Application Scenarios of Internet of Emergency Services
### Disaster Response  
Disaster response is one of the most critical applications of the Internet of Emergency Services (IoES) [74, 75, 132]. The IoES can help responders quickly and effectively manage disasters, reduce response times, and save lives [25, 139]. In this scenario, the IoES integrates various technologies, such as IoT devices, cloud computing, AI, GIS, wearables, and UAVs, to provide a comprehensive solution for disaster response. One real-world example of the IoES in disaster response is the use of IoT devices in earthquake detection and early warning systems. In Mexico City, the government has installed more than 12,000 seismic sensors that detect earthquakes in real-time. The data from these sensors is transmitted to the city's emergency management center, where it is analyzed to determine the magnitude and location of the earthquake. The center can then quickly dispatch response teams to the affected areas and alert citizens through mobile apps and other communication channels. Another example is the use of drones in disaster response. In the aftermath of Hurricane Harvey in 2017, the Federal Aviation Administration (FAA) authorized the use of drones to survey the damage and assess the needs of affected communities. Drones equipped with cameras and other sensors were used to capture images and videos of the disaster area, which were then analyzed using AI and GIS technologies. These data helped responders identify areas of the greatest need and prioritize their response efforts. The IoES can also help responders coordinate their efforts and communicate more effectively. In the case of a wildfire, for example, wearables can be used to track the location and health status of firefighters. Real-time data from these devices can be transmitted to the emergency management center, which can then deploy additional resources as needed. GIS technologies can be used to map the fire and identify areas that need to be evacuated. AI algorithms can analyze weather data and predict the spread of the fire, allowing responders to make informed decisions about where to focus their efforts. Furthermore, the IoES can provide post-disaster support to affected communities. For example, data analytics can be used to identify areas that are most vulnerable to future disasters, allowing local governments to take proactive measures to prevent or mitigate the impact of future disasters. Blockchain technology can be used to track the distribution of aid and ensure that it reaches those who need it most. Further, we present a real-world example of the Disaster Management scenario. A hurricane has hit a coastal town, causing widespread damage and flooding. The Emergency Management Center (EMC) receives multiple emergency requests from residents who are stranded and in need of assistance. The IoES is activated to coordinate the emergency response. The EMC uses the IoES to collect data from various sources, including IoT devices, weather sensors, and social media feeds, to assess the extent of the damage and identify areas that require immediate assistance. The EMC dispatches response teams, including search and rescue teams, medical teams, and National Guard units, to the affected areas. IoT devices installed in buildings and infrastructure provide real-time data on the status of