## 1 Introduction
Additionally, our paper elaborates on a generic IoT-enabled EEWS architecture, discusses drones' role in disaster management, and provides a summary of the primary verification and validation (V&V) methods required for the systems under consideration. Finally, the paper describes research gaps in this research domain and provides future directions. While previous papers have discussed geospatial technologies, remote sensing, and social media platforms' use in earthquake research, disaster management, and catastrophe response, our paper focuses on the role of IoT and cloud infrastructure in EEWS and provides a comprehensive overview of the many elements needed to realize an EEWS. Table 1 is intended to provide a comparison of our work with previous works in the field of earthquake research and disaster management. It summarizes the main focus, methodology, and contributions of each paper, highlighting the unique contributions of our work in relation to other research in this domain. \begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Ref.** & **Utilized Technology** & **Main Focus** & **Methodology** & **Contributions** \\ \hline
[86] & Geophysical technology & Earthquake and catastrophe management & Literature review & Earthquake hazard, vulnerability, risk analysis \\ \hline
[87] & Remote sensing & Earthquake management & Review of remote sensing applications & Remote sensing pros and cons in earthquake research \\ \hline
[88] & UAV hardware & Disaster relief & Field trials and case studies & Implementable framework for drone data collection and analysis for disaster preparedness, response, and recovery \\ \hline
[89] & IoT technology & Disaster management & Comparative analysis of IoT-based disaster management options & Practical applications of IoT technology for disaster management \\ \hline
[90] & Modern technology & Disaster and risk management & Evaluation of available and applied technology & Suggestions for improving technology adoption across all DRM pillars \\ \hline
[91] & Mapping techniques & Mapping in post-earthquake settings & Evaluation of ML and deep learning frameworks & Identification of research gaps and possibilities for real-world scenarios \\ \hline
[92] & Remote sensing & Remote sensing data and methods for earthquake risk assessment & Review of remote sensing applications & Necessity for a complete, interdisciplinary approach to earthquake risk assessment \\ \hline
[93] & Satellite images & EEWS & Literature review & Evaluation of current and potential applications of remote sensing for seismic disaster early warning \\ \hline
[94] & Remote sensing & Post-earthquake damage assessment & Case studies and literature review & Identification of challenges and opportunities in remote sensing for post-earthquake damage assessment \\ \hline
[95] & Emerging technologies & Disaster management & Literature review and text mining & Analysis of the effects of emerging technologies on disaster management \\ \hline
[96] & Digital tools & Managing existing structures in earthquake settings & Case study & Procedure for managing pre- and post-earthquake stages of existing structure management using digital tools \\ \hline Our Work & IoT nodes and cloud infrastructure & EEWS, environment type, data type, and source, measurement parameters, cloud infrastructure & Literature review and analysis & Comprehensive overview of the role of IoT and cloud infrastructure in EEWS, including a generic architecture and verification and validation methods \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of our work with previous works. The following is a list of the key contributions that the paper makes, highlighting the various points of innovation:  
* We clarify why the EEWS is advantageous for smart cities. * We emphasize the growth of IoT usage, as well as the IoT system framework in general and its constituent parts.