## 4 Use Cases and Application Scenarios of Internet of Emergency Services
### Outline
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**References** & **Scenario** & **Contect of Use** & **Description** \\ \hline [PERSON] et al. [99] & Chronic diseases & Remote patients & Proposed ML-ART framework for remote triage of patients using machine learning \\ \hline [PERSON] et al. [137] & Emergencies during smart cities & Smart cities & Review of literature on smart technologies during emergencies in smart cities \\ \hline [PERSON] and [PERSON] [138] & Building fires & Urban emergencies & Use of big data and IoT in emergency management of urban fires \\ \hline [PERSON] et al. [139] & Rainstorm-induced emergencies & Rainstorm disasters & Development of a cross-domain transfer learning framework for emergency recognition using text reports \\ \hline [PERSON] et al. [40] & Natural disasters in urban areas & Use of smart city middleware & Development of smart city middleware for HADR operations \\ \hline [PERSON] et al. [49] & Disaster response & Real-time bio-signal sensor monitoring & Integration of health monitoring sensors suitable for detecting stress, anxiety and physical fatigue in an Internet of Cooperative Agents architecture \\ \hline [PERSON] et al. [140] & Disaster management in smart cities & IoT-enabled energy aware metaheuristic clustering with routing protocol & YSGF-C technique to elect cluster heads and organize clusters; ECSO-MIR approach for optimal route selection \\ \hline [PERSON] et al. [50] & Building fire emergencies & Goal-Directed Task Analysis & Determination of fire emergency responders’ Situational Awareness (SA) Goals, Decisions, and Information (GDI) requirements \\ \hline [PERSON] et al. [132] & Category 1 emergency services & On-demand computing resources & Identification of challenges faced by stakeholders involved in incident response and formulation of future requirements for an improved system \\ \hline [PERSON] et al. [25] & Natural Disasters & IoT-based infrastructure of civilians and lets participants act as both information producers and consumers. Between evacuees, first aid teams, and the emergency operation center in charge of the operation, and the infrastructure serves as a link. Both actual measurements and simulations were used to assess the solution. \\ \hline [PERSON] and [PERSON] [41] & Natural, Technological, and Man-made Disasters & Industry 4.0 technologies & Using Industry 4.0 technology across many activities is a strategy for improving coordination in humanitarian supply chains. It maps the measurements of coordination with essential success elements. \\ \hline [PERSON] et al. [23] & Panic Events & Multimodal dataset & Multimodal dataset contains biometric and spatiotemporal information for the identification of the panic state in participants who engage in a variety of activities throughout time. The dataset was used to train a variety of machine learning models to differentiate between normal behavior and panic situations. \\ \hline [PERSON] and [PERSON] [84] & Emergencies in Industrial Zones & UAV-mounted cloudlet systems & UAV-mounted cloudlet systems \\ \hline \hline \end{tabular}
\end{table} 
Table 13: Summary of scenarios in emergency management and response.