## 4 Use Cases and Application Scenarios of Internet of Emergency Services
### Medical Emergency  
The Medical Emergency scenario in The Internet of Emergency Services (IoES) involves the use of advanced technologies to improve the emergency medical response [77; 99; 119; 142; 143]. In this scenario, the IoES leverages the Internet of Things (IoT) and other technologies to collect and analyze data in real-time, provide timely and accurate medical assistance to patients, and enhance the overall emergency medical response. One of the most critical components of the Medical Emergency scenario is the use of wearable devices. These devices can monitor a patient's vital signs, such as heart rate, blood pressure, and oxygen saturation, and transmit that information in real-time to emergency medical services (EMS) personnel. These data can help EMS personnel make more informed decisions about how to treat the patient and provide a more targeted response. For example, if a patient's heart rate is elevated, EMS personnel can administer medication to lower the heart rate, potentially preventing a more serious medical event. Another key component of the Medical Emergency scenario is the use of AI technologies. AI algorithms can analyze large amounts of data from various sources, including wearable devices, electronic health records, and medical imaging, to help medical professionals make more informed decisions about patient care. For example, AI algorithms can detect patterns in a patient's vital signs that may indicate the onset of a serious medical condition, allowing medical professionals to take action before the condition worsens. Real-world examples of the Medical Emergency scenario in action can be found in a variety of settings. For instance, in the United States, the city of New York has implemented an EMS telemedicine program that uses advanced technologies to provide remote medical consultations to patients in need. The program utilizes wearable devices to monitor patients' vital signs and transmit that information in real-time to a remote medical professional, who can then provide guidance to EMS personnel on how to treat the patient. Another example can be found in the Netherlands, where the Dutch Heart Foundation has launched a project to develop a smartwatch that can detect the early signs of a heart attack. The smartwatch monitors a patient's heart rate, blood pressure, and other vital signs, and uses AI algorithms to detect changes that may indicate the onset of a heart attack. If the watch detects such changes, it can alert emergency services, who can then dispatch medical personnel to the patient's location. Further, we discuss an example of the Medical Emergency scenario (Figure 6) in The Internet of Emergency Services (IoES):  
1. User/Citizen detects symptoms of a heart attack and uses their smartphone to call emergency services. 2. The call is received by the Emergency Management Center (EMC), where an operator quickly identifies the location of the user/citizen and the nature of the emergency. 3. The EMC dispatches an ambulance to the user/citizen's location, and also sends a notification to nearby healthcare providers and hospitals to prepare for the arrival of the patient. 4. The IoT devices located in the user/citizen's home or wearable devices are used to monitor the user/citizen's vital signs, such as heart rate and blood pressure, and transmit the data to the EMC in real-time. 5. The ambulance arrives at the user/citizen's location and is equipped with advanced medical equipment, such as a defibrillator and electrocardiogram machine, that can transmit data to the EMC and healthcare providers in real-time. 6. The EMC uses artificial intelligence (AI) algorithms to analyze the data collected from the IoT devices and ambulance equipment to predict the user/citizen's condition and recommend treatment options to the healthcare providers. 7. The healthcare providers use the recommended treatment options to stabilize the user/citizen's condition and transport them to the nearest hospital. 8.