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Analysis of Earthquake Emergency Command System According to Cloud Computing Methods
- Source :
- IEEE Access, Vol 9, Pp 146970-146983 (2021)
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- An earthquake emergency command system is designed based on cloud computing and the Internet of Things (IoT) to mitigate slow information acquisition, low processing efficiency, and weak information storage and communication ability in earthquake rescue. First, cloud computing technology is introduced, and a traditional earthquake emergency command system is analyzed comprehensively. Then, the characteristics of midwave infrared remote sensing data are explored before and after recent earthquakes in China based on satellite remote sensing data. Subsequently, a new earthquake emergency command system is built based on cloud computing and IoT technology along with data from satellite midwave infrared remote sensing. Finally, system feasibility is evaluated. The results show that surface radiation changes significantly before an earthquake; infrared brightness and temperature fluctuates drastically; and the abnormal region gradually approaches the epicenter of the earthquake. The peak value of the relative power spectrum in the earthquake is more than 9 times the average. In conclusion, the proposed emergency command system based on satellite remote sensing data, cloud computing, and IoT can yield good evaluation results (5.36), demonstrating that multidimensional satellite thermal infrared remote sensing data analysis can improve the accuracy of earthquake prediction. The proposed earthquake emergency command system based on satellite remote sensing data combined with cloud computing and IoT technology can also provide a basis for optimizing earthquake rescue strategies.
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- Directory of Open Access Journals
- Journal :
- IEEE Access
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.3af8e28237d647729baf5ff58346f2b9
- Document Type :
- article
- Full Text :
- https://doi.org/10.1109/ACCESS.2020.3019833