Analysis of Earthquake Emergency Command System According to Cloud Computing Methods

Abstract

To solve the problems of slow information acquisition, low processing efficiency, weak information storage and communication ability in earthquake rescue, an earthquake emergency command system on the basis of cloud computing and Internet of Things (IoT) is designed. First, the cloud computing technology is introduced, and the traditional earthquake emergency command system built by cloud computing and the Internet of things is analyzed. Then, based on the satellite remote sensing data, the characteristics of the middle-wave infrared remote sensing data before and after the recent earthquakes in China are explored. Subsequently, a new earthquake emergency command system is built based on cloud computing and Internet of things technology along with the data from the satellite middle-wave infrared remote sensing. Finally, the feasibility of the system is evaluated. The results show that the surface radiation changes significantly before the earthquake, the infrared brightness temperature difference value also fluctuates violently, and the abnormal area will gradually get closer to the epicenter as time goes by. The peak value of the relative power spectrum in the earthquake is more than 9 times of the average value in the normal time. In conclusion, the evaluation result of the emergency command system based on satellite remote sensing data, cloud computing, and Internet of things is good, suggesting satellite infrared remote sensing data can be applied to earthquake prediction, and the earthquake emergency command system constructed combining cloud computing and Internet of things technology has a good feasibility.

Research on Key Technologies of Earthquake Emergency Response Based on Multi-Sensor Data

“…When the remote sensing images before and after the earthquake are of the same origin, a method based on the correlation change detection of principal components of multiple texture features is proposed, which makes full use of the rich texture features in the image and avoids the redundancy of information; When remote sensing images before and after earthquakes are of different sources, a post-classification change detection method based on object-oriented combination is proposed to overcome the requirements of traditional change detection for data type and time consistency, and realize multi-sensor data assimilation and information collaborative processing [5][6]. When a large earthquake occurs, strengthening the analysis and research of geological structure background will help to scientifically explain the cause of the earthquake.…”