Research on cellular fleets for wildfires’ surveillance based on anti-entropy weight method

Dawei Peng; Yi Luo; Xutong Liu

doi:10.1117/12.2641851

10 November 2022 Research on cellular fleets for wildfires’ surveillance based on anti-entropy weight method

Dawei Peng, Yi Luo, Xutong Liu

Proceedings Volume 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022); 123482G (2022) https://doi.org/10.1117/12.2641851
Event: 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 2022, Zhuhai, China

Abstract

In order to find locations where wildfires are more likely to occur in many forest areas in Victoria, this paper establishes a wildfire risk assessment model. This paper uses the anti-entropy method to analyze the Fire Radiative Power, Normalized Difference Vegetation Index, and Forest Fire Danger Index to obtain the Surveillance Rank Index, which is used comprehensive evaluation of the possibility and scale of forest fires in a certain place. Then, this paper uses SRI and k- Means Clustering to divide Victoria into several small areas, and performed gradient analysis on each small area to obtain each priority detection sequence of regions in a cluster. Finally, this paper establishes a complete multi-drone cooperative surveillance model to plan the path of drones and select the hovering position of the drones carrying repeater. Therefore, with considering the interference of high-altitude areas to the communication range of radio relay drones, Victoria needs a total of 761 drones, consisting of 639 SSA drones and 122 radio relay drones.

Citation Download Citation

Dawei Peng, Yi Luo, and Xutong Liu "Research on cellular fleets for wildfires’ surveillance based on anti-entropy weight method", Proc. SPIE 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 123482G (10 November 2022); https://doi.org/10.1117/12.2641851

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