Abstract
Climate-related natural disasters have affected the lives of thousands of people. Global warming creates warmer and drier conditions which increase the risk of wildfires. In large-scale disasters such as wildfires, search and rescue (SAR) operations become extremely challenging due to low visibility, difficulty to breath, and high temperature from fire and smoke. Unmanned aerial vehicles (UAVs), such as drones, have been used to support such operations. In our previous work, a Krypto module is proposed to “sniff” out wireless signals from mobile phones to locate any possible survivors. With the increased popularity of drones, it is possible to allow people to volunteer in SAR operations with their drones. In this paper, we propose an Open Collaborative Platform for multiple drones to assist SAR operations. The open platform manages different searching drones that carry the Krypto module to collaborate by sharing information and planning search paths/areas. With our Open Collaborative Platform, anyone can participate in SAR operations and contribute to finding possible survivors. The novelty of this work is the openness and collaboration of the platform that “crowdsourcing” the searching operation to a large group of people who share information and contribute to finding possible survivors in a large disaster such as wildfires. Our experimental study shows that the Open Collaborative Platform is effective in reducing both the number of drones required and the search time for finding survivors.
Funder
Taiwan Ministry of Science and Technology
Subject
Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering
Reference45 articles.
1. Centre for Research on the Epidemiology of Disasters, “Disaster Year in Review 2020”
https://cred.be/sites/default/files/CredCrunch65.pdf
2. Wildfires
https://www.who.int/health-topics/wildfires#tab=tab_1
3. Krypto: Assisting Search and Rescue Operations using Wi-Fi Signal with UAV;Ho,2015
4. Krypto Source Code
https://github.com/NTNUNSL/WIFILocatedDrone
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