Employing Machine Learning and IoT for Earthquake Early Warning System in Smart Cities

Mohamed S. Abdalzaher (), Hussein A. Elsayed, Mostafa M. Fouda () and Mahmoud M. Salim
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Mohamed S. Abdalzaher: Department of Seismology, National Research Institute of Astronomy and Geophysics, Cairo 11421, Egypt
Hussein A. Elsayed: Department of Electronics and Communications Engineering, Ain Shams University (ASU), Cairo 11566, Egypt
Mostafa M. Fouda: Department of Electrical and Computer Engineering, College of Science and Engineering, Idaho State University, Pocatello, ID 83209, USA
Mahmoud M. Salim: Department of Electronics and Communications Engineering, October 6 University (O6U), Giza 12585, Egypt

Energies, 2023, vol. 16, issue 1, 1-22

Abstract: An earthquake early warning system (EEWS) should be included in smart cities to preserve human lives by providing a reliable and efficient disaster management system. This system can alter how different entities communicate with one another using an Internet of Things (IoT) network where observed data are handled based on machine learning (ML) technology. On one hand, IoT is employed in observing the different measures of EEWS entities. On the other hand, ML can be exploited to analyze these measures to reach the best action to be taken for disaster management and risk mitigation in smart cities. This paper provides a survey on the different aspects required for that EEWS. First, the IoT system is generally discussed to provide the role it can play for EEWS. Second, ML models are classified into linear and non-linear ones. Third, the evaluation metrics of ML models are addressed by focusing on seismology. Fourth, this paper exhibits a taxonomy that includes the emerging ML and IoT efforts for EEWS. Fifth, it proposes a generic EEWS architecture based on IoT and ML. Finally, the paper addresses the application of ML for earthquake parameters’ observations leading to an efficient EEWS.

Keywords: machine learning; Internet of Things; earthquake early warning system; smart city management; disaster management (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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