## 1 Introduction
For instance, satellite systems have been used to track earthquake movements, and IoT sensors have been used to detect earthquakes and provide early warnings. Furthermore, 5G and SDN technologies have been deployed for real-time communication and data transmission in emergency situations. These technologies have greatly enhanced the accuracy and speed of earthquake detection and warning systems and have improved the response time of emergency services. Moreover, the integration of robots and the internet has the potential to be a significant breakthrough in this field. According to [35], a new integrated system named \"robot-event\" has been proposed, which is able to execute autonomous inspections and emergency responses to a severe event. The robot uses real-time image tracking to inspect the indoor environment and help any human victims found on the ground. It operates in structurally sound houses with moderate damage, focusing on situations where people are at risk from falling furniture. The system was tested indoors to assess its functionality and operation alongside a smart EEWS. This new technology has the potential to significantly reduce the risk of human casualties during an earthquake by providing timely and accurate information to emergency responders. Future research in this area could explore further the use of robotics, artificial intelligence, and the internet to develop more advanced and efficient EEWSs. The research conducted in the literature regarding remote sensing applications facilitated by satellite communication systems did not cease with the studies by [36; 37]. It also encompassed NFV and SDN, which involved gateways via IoT as well as Micro-Electro-Mechanical systems (MEMS), as noted in [38; 39; 40; 41]. The primary objective of this endeavor was to provide relief to areas that had suffered damage or destruction on a large scale. Virtualization played a critical role in this, as it could help mitigate the risks posed by natural disasters. As highlighted in [42], such networks must be designed to optimize node lifetimes. In addition, ref. [43] presented a tragic scenario that showcased an EEWS designed to facilitate a safe evacuation plan against disaster risks by combining cloud-based IoT with heterogeneous networks. Similarly, the combination of IoT and current communication technologies and techniques could prove to be crucial in ensuring the smooth and secure transfer of data, as stated in [44; 45; 46; 47; 48; 49]. The studies mentioned here are accompanied by conventional approaches to earthquake detection and analysis, as well as methods for distinguishing between different types of fault ruptures, which have been extensively investigated in the relevant academic literature [50]. In [51], a local similarity earthquake detection approach based on the near est neighbor method was proposed to determine whether an earthquake had occurred by examining the consistency of received signals from the nearest neighbors of targeted stations and their closest neighbors. On the other hand, refs. [52; 53] focused more on determining the earthquake's amplitude in the first few seconds of its occurrence rather than the complete rupture. However, conventional methods take a significant amount of time to calculate earthquake parameters [54], highlighting the need for additional efforts and studies. Early research suggests that it is possible to accurately predict the magnitude and depth of an earthquake using a graph CNN model that employs batch normalization and attention mechanism techniques. This model can be used in any location with any seismic nodes. The variability of seismic waves and the complexity of the Earth's structure suggest that there is ample room for innovative and adaptable solutions. With the help of modern technologies, the impact of earthquakes on the studied region in [54] can be significantly reduced. An increasingly useful technology for disaster management is drones.