Low-power image stitching management for reducing power consumption of UAVs for disaster management system

Recently, unmanned aerial vehicles (UAVs) are used for disaster management system that monitors disasters (e.g., forest fire and landslide) of some areas (e.g., mountains) and responds to disasters. The UAVs of the disaster management system take images and sensor data (e.g., temperature and humidity data) of the areas where the disasters can occur, and then the disaster management system stitches the images of the areas to monitors the areas. This paper proposes the low-power image stitching management (LPISM) that can reduce power consumptions of the UAVs that take images for image stitching in the disaster management system. The disaster management system with the LPISM generates the least number of waypoints for the UAV to take images for image stitching. Therefore, the UAVs can reduce power consumption for taking images, and the UAV can increase the frequency of gathering sensor data for monitoring disasters in detail. The gathered sensor data can be used for multi-modal data convergence analysis in order to respond dangerous situations.