Flood Disaster Identification and Decision Support System using Crowdsource Data Based on Convolutional Neural Network and 3S Technology

Authors

  • Supattra Puttinaovarat Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Thailand
  • Teerawad Sriklin Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Thailand
  • Sompop Dangtia Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Thailand
  • Kanit Khaimook Ramkhamhaeng University, Bangkok, Thailand

DOI:

https://doi.org/10.3991/ijim.v14i20.17243

Keywords:

Flood Identification, CNN, Crowdsource Data, GIS

Abstract


Every flood causes damages to many lives and properties. Moreover, it affects the economy and lifestyle of people in the society in a short period and a long period. In consequence, this research would demonstrate techniques and flood detection analyzed through digital images and web application development for receiving reports and inspection of flood situation in every area. The process requires crowdsource data and uses 3S technology so it will receive the accurate and real-time data for making a decision in the flood management and aids to the people in the disastrous area. In this research, Convolutional neural network was applied for flood detection and classification using digital images and data from people or the victims. According to the study, it was found that convolutional neural network for flood classification has accuracy of data at the high level or 95.50%, 93.00%, 97.89%, and 0.91 which are the results of accuracy, producer accuracy, user accuracy, and kappa statistics, respectively. Besides, the use of this technique saves cost, time, and labors. Furthermore, the method could be applied to other disasters such as landslide, earthquake, and fire. It is able to monitor the incident in each type of disasters and also examines the damaged site after the incident.

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Published

2020-12-11

How to Cite

Puttinaovarat, S., Sriklin, T., Dangtia, S., & Khaimook, K. (2020). Flood Disaster Identification and Decision Support System using Crowdsource Data Based on Convolutional Neural Network and 3S Technology. International Journal of Interactive Mobile Technologies (iJIM), 14(20), pp. 117–134. https://doi.org/10.3991/ijim.v14i20.17243

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Section

Papers