Employing Remote Sensing, Data Communication Networks, AI, and Optimization Methodologies in Seismology

Abstract

Seismology is among the intrinsic sciences that strictly affect human lives. Many research efforts are presented in the literature aiming at achieving risk mitigation and disaster management. More particularly, modern technologies have been employed in such a pivot. However, the day-to-day challenges and complexities of such natural science that face the stack holders still need more reliable and intelligent solutions. The solution can depend on a partial or integrated system of modern technologies. In this article, we extensively survey the corelated modern technologies aiming to gather the major efforts exerted in this regard. It also outlines the desirability of seismology to modern technologies. Then, we present a detailed analysis of remote sensing and data communication networks (DCNs), which are considered the backend of seismic networks. Furthermore, for seismology, we depict both classical and nonclassical approaches based on DCN principles, such as optical fiber-based acoustic sensors, social media, and the Internet of things (IoT). Following that, a comprehensive description of the various optimization techniques utilized for seismic wave analysis and for prolonging network lifetime is offered. A description of the important functions that artificial intelligence (AI) can play in different fields of seismology is also included. Finally, we present some recommendations for stack holders to prevent natural calamities and preserve human lives.

Keywords

• Data communication networks (DCNs)
• deep learning
• Internet-of-things (IoT)
• machine learning
• optimization techniques
• seismology