## 3 Research Framework of Internet of Emergency Services
### Real-Time Data Collection and Analysis
#### 3.3.4 Augmented Reality/Virtual Reality (AR/VR)
The use of AR/VR in emergency response and management has the potential to revolutionize the way we prepare for and respond to disasters. By providing realistic and interactive training simulations, supporting decision making during response operations, and enhancing situational awareness for responders, AR/VR can help improve response times, increase effectiveness, and ultimately save lives. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** & **VR or AR** & **Context of Use** & **Description of Use** \\ \hline \hline \multirow{7}{*}{[PERSON] and [PERSON] [60]} & \multirow{7}{*}{AR} & \multirow{7}{*}{Indoor emergency evacuation} & \multirow{7}{*}{Proposed a machine-learning-based indoor AR navigation and emergency evacuation system that guides optimal escape paths for individual users. Uses IoT-enabled ad hoc network for emergency event detection and sensing data delivery, and a hybrid reinforcement-learning-based routing algorithm for data delivery. Predicts disaster propagation with a simple disaster area prediction method and estimates user location using a deep neural network. Derives the optimum evacuation path for each individual using a novel model-based Q-learning method. Evaluated experimentally for various disaster scenarios. \\ \hline \multirow{7}{*}{[PERSON] and [PERSON] [111]} & \multirow{7}{*}{VR} & \multirow{7}{*}{Remote learning and panic, well-being and determination and pedestrian} & \multirow{7}{*}{\begin{tabular}{} \end{tabular} } \\  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \hline \hline \multirow{7}{*}{[PERSON], et al. [29]} & \multirow{7}{*}{AR} & \multirow{7}{*}{Dissaster detection and early IoT detection} & \multirow{7}{*}{\begin{tabular}{} \end{tabular} } \\  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \hline \hline \multirow{7}{*}{[PERSON], et al. [112]} & \multirow{7}{*}{AR} & \multirow{7}{*}{Human monitoring system in industrial use} & \multirow{7}{*}{\
\begin{tabular}{} \end{tabular} } \\  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \hline \hline
\begin{tabular}{} \end{tabular} \\ \end{tabular}
\end{table} 
Table 8: The use of Augmented Reality and Virtual Reality for emergency monitoring and disaster response. 3.3.5. Challenges and Limitations of Real-Time Data Collection and Analysis for Emergency Management and Response  
Real-time data collection and analysis have become increasingly important in emergency management and response. However, there are still several challenges and limitations associated with these processes, as follows:  
* Data Quality: The accuracy and reliability of real-time data can be affected by various factors, including technical limitations, human errors, and environmental conditions. Inaccurate or incomplete data can lead to incorrect decisions and actions, which can have serious consequences. * Data Overload: Real-time data collection can result in a large volume of information, which can be overwhelming for emergency responders to process and analyze. This can lead to delays in decision making and response times, which can impact the effectiveness of emergency management. * Privacy and Security: Real-time data collection can also raise privacy and security concerns, particularly when personal information is involved. The appropriate measures need to be put in place to ensure the security and confidentiality of the data being collected and analyzed [114]. * Technical Limitations: Real-time data collection and analysis require the use of advanced technologies and tools, which can be expensive and require specialized skills and expertise. This can create technical limitations for smaller emergency management agencies or those with limited resources.