Integrated smart robot with earthquake early warning system for automated inspection and emergency response

2021 ◽  
Author(s):  
Tzu-Hsuan Lin ◽  
Jing-Ting Huang ◽  
Alan Putranto
2021 ◽  
Author(s):  
Tzu-Hsuan Lin ◽  
Jing-Ting Huang ◽  
Alan Putranto

Abstract The natural hazard, mainly earthquake, has caused substantial economic losses and human life loss to many countries. Taiwan, which is located on the western Circum-Pacific seismic belt, has encountered the problem as mentioned earlier in Meishan, Hsinchu-Taichung, and Chi-Chi earthquakes a few years ago. In this study, the researchers propose a novel robot-event integrated system capable of doing the automated inspection and emergency response due to a significant earthquake. When the household’s earthquake warning receiving device picks up an alert, its built-in wireless communications system will send a signal to the robot. The robot commences inspection of the indoor area via real-time image recognition and tracking. It will approach them upon detecting fallen people, regulating their movements via a robot operating system (ROS) monitoring interface. The robot is designed to operate in a house that remains standing with acceptable damage in which the furniture might falling and injure the occupants after an earthquake hit. The indoor experiment conducted to verify the robot system and operation with a designed condition such as fallen and non-fallen people as a detected object. The robot tested to deliver food or medicine for fallen people while waiting for rescuers to arrive. Tests indicate that the proposed smart robot has prospective implementation to the real-world application with more research and development. The smart robot integrated with an earthquake early warning system has a promising approach to the temporary care of people affected by earthquakes.


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.


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

2021 ◽  
Author(s):  
Bita Najdahmadi ◽  
Marco Pilz ◽  
Dino Bindi ◽  
Hoby Njara Tendrisoa Razafindrakoto ◽  
Adrien Oth ◽  
...  

<p>The Lower Rhine Embayment in western Germany is one of the most important areas of earthquake recurrence north of the Alps, facing a moderate level of seismic hazard in the European context but a significant level of risk due to a large number of important industrial infrastructures. In this context, the project ROBUST aims at designing a user-oriented hybrid earthquake early warning and rapid response system where regional seismic monitoring is combined with smart, on-site sensors, resulting in the implementation of decentralized early warning procedures.<br><br>One of the research areas of this project deals with finding an optimal regional seismic network arrangement. With the optimally compacted network, strong ground movements can be detected quickly and reliably. In this work simulated scenario earthquakes in the area are used with an optimization approach in order to densify the existing sparse network through the installation of additional decentralized measuring stations. Genetic algorithms are used to design efficient EEW networks, computing optimal station locations and trigger thresholds in recorded ground acceleration. By minimizing the cost function, a comparison of the best earthquake early warning system designs is performed and the potential usefulness of existing stations in the region is considered as will be presented in the meeting.</p>


Sign in / Sign up

Export Citation Format

Share Document