An IoT-Based Earthquake Warning System for Smart Cities

2019 ◽  
pp. 208-227
Author(s):  
Suja Priyadharsini S. ◽  
Ramalakshmi S.
Keyword(s):  
Internet Of Things ◽  
Early Warning ◽  
Early Warning System ◽  
Smart Cities ◽  
Warning System ◽  
Earthquake Magnitude ◽  
Transfer Data ◽  
Earthquake Early Warning System ◽  
The Individual ◽  
Magnitude Determination

Earthquakes are the most common natural disasters that occur in India. An earthquake warning system minimizes damage and saves countless lives. A seismic wave analysis helps develop an early warning system. The bigger the earthquake, the stronger the shaking. Hence, magnitude determination is critical to developing an earthquake early warning system. The chapter deals with detecting earthquake magnitude by identifying the individual magnitude of earthquakes. An early warning system can be effectively implemented by the proposed method, along with high-end processors and the IoT (internet of things), which has the ability to collect and transfer data over networks with no manual intrusion. The proposed early earthquake warning (EEW) system can be used to support the development of smart cities so earthquake-prone zones are made less susceptible to disaster.

Blockchain of Internet of Things-Based Earthquake Alarming System in Smart Cities

2021 ◽  
pp. 272-287
Author(s):  
Kuldeep Singh Kaswan ◽  
Jagjit Singh Dhatterwal ◽  
Krishan Kumar
Keyword(s):  
Internet Of Things ◽  
Early Warning ◽  
Early Warning System ◽  
Smart Cities ◽  
Warning System ◽  
S Wave ◽  
S Waves ◽  
Natural Catastrophes ◽  
Intelligent Cities ◽  
The Waves

The worst natural catastrophes occurring in well-settled intelligent cities are earthquakes. A framework of earthquake warning minimizes destruction and protects countless lives. A system built on IoT to identify the earthquake in the S waves and then to warn people by showing them an alert and where the earthquake happened is proposed. An early warning system is generated by a seismic wave survey. The larger the earthquake, the heavier the tremor. The waves are also breaking down the driveway. So the earthquake in the S wave is safer to find. Therefore, determining the extent of the early warning system is essential for creating an earthquake. The chapter addresses the detection of the frequency of earthquakes by identifying the size of earthquakes. In this chapter, we will discuss the elevated processors and IoT (internet of things) that can efficiently deploy an early warning device that can capture and transmit data over networks without manual interference. The early earthquake warning system (EEW) can be used to support smart urban planning, making earthquake areas less sensitive to disasters.

scholarly journals Feasibility study of earthquake early warning in Tehran, Iran

2021 ◽  
Author(s):  
S. Enferadi ◽  
Z. H. Shomali ◽  
A. Niksejel
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Disaster Mitigation ◽  
Lead Times ◽  
Worst Case ◽  
Earthquake Parameters ◽  
Earthquake Early Warning System ◽  
Earthquake Scenarios

AbstractIn this study, we examine the scientific feasibility of an Earthquake Early Warning System in Tehran, Iran, by the integration of the Tehran Disaster Mitigation and Management Organization (TDMMO) accelerometric network and the PRobabilistic and Evolutionary early warning SysTem (PRESTo). To evaluate the performance of the TDMMO-PRESTo system in providing the reliable estimations of earthquake parameters and the available lead-times for The Metropolis of Tehran, two different approaches were analyzed in this work. The first approach was assessed by applying the PRESTo algorithms on waveforms from 11 moderate instrumental earthquakes that occurred in the vicinity of Tehran during the period 2009–2020. Moreover, we conducted a simulation analysis using synthetic waveforms of 10 large historical earthquakes that occurred in the vicinity of Tehran. We demonstrated that the six worst-case earthquake scenarios can be considered for The Metropolis of Tehran, which are mostly related to the historical and instrumental events that occurred in the southern, eastern, and western parts of Tehran. Our results indicate that the TDMMO-PRESTo system could provide reliable and sufficient lead-times of about 1 to 15s and maximum lead-times of about 20s for civil protection purposes in The Metropolis of Tehran.

The First Stage of an Earthquake Early Warning System in South Korea

2017 ◽  
Vol 88 (6) ◽  
pp. 1491-1498 ◽  
Author(s):  
Dong‐Hoon Sheen ◽  
Jung‐Ho Park ◽  
Heon‐Cheol Chi ◽  
Eui‐Hong Hwang ◽  
In‐Seub Lim ◽  
...  
Keyword(s):  
South Korea ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Earthquake Early Warning System
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