scholarly journals Analysis of dynamic path loss based on the RSSI model for rupture location analysis in underground wireless sensor networks and its implications for Earthquake Early Warning System (EEWS)

2015 ◽  
Vol 5 (3) ◽  
pp. 183-195 ◽  
Author(s):  
Dutta Pushan Kr
Author(s):  
S. Enferadi ◽  
Z. H. Shomali ◽  
A. Niksejel

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.


2013 ◽  
Vol 427-429 ◽  
pp. 1268-1271
Author(s):  
Xue Wen He ◽  
Ying Fei Sheng ◽  
Kuan Gang Fan ◽  
Le Ping Zheng ◽  
Qing Mei Cao

In view of the existing flaws of traditional manual observations, a new type of tailing reservoir safety monitoring and warning system based on ZigBee and LabVIEW was designed. The system chose SoC chip CC2530 as the RF transceiver and designed the low-power wireless sensor networks nodes to collect and process the data of tailing reservoir. It chose ZigBee 2007 as the network communication protocol, and uploaded the data to PC by RS232 serial port. The monitoring and warning interface of PC was completed with LabVIEW. The testing results show that the data transmission of the network is stable and the system is suitable for real-time monitoring and warning of the tungsten tailing reservoir.


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