Active Wildfires Detection and Dynamic Escape Routes Planning for Humans through Information Fusion between Drones and Satellites
December 06, 2023 Β· Declared Dead Β· π 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
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Authors
Chang Liu, Tamas Sziranyi
arXiv ID
2312.03519
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CV
Citations
3
Venue
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Last Checked
4 months ago
Abstract
UAVs are playing an increasingly important role in the field of wilderness rescue by virtue of their flexibility. This paper proposes a fusion of UAV vision technology and satellite image analysis technology for active wildfires detection and road networks extraction of wildfire areas and real-time dynamic escape route planning for people in distress. Firstly, the fire source location and the segmentation of smoke and flames are targeted based on Sentinel 2 satellite imagery. Secondly, the road segmentation and the road condition assessment are performed by D-linkNet and NDVI values in the central area of the fire source by UAV. Finally, the dynamic optimal route planning for humans in real time is performed by the weighted A* algorithm in the road network with the dynamic fire spread model. Taking the Chongqing wildfire on August 24, 2022, as a case study, the results demonstrate that the dynamic escape route planning algorithm can provide an optimal real-time navigation path for humans in the presence of fire through the information fusion of UAVs and satellites.
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