The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Download
Citation
Articles | Volume XLII-3/W8
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W8, 485–489, 2019
https://doi.org/10.5194/isprs-archives-XLII-3-W8-485-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W8, 485–489, 2019
https://doi.org/10.5194/isprs-archives-XLII-3-W8-485-2019

  23 Aug 2019

23 Aug 2019

A FUZZY LOGIC APPROACH FOR DRONE CAPABILITY ANALYSIS ON DISASTER RISK ASSESSMENT

P. Zlateva1, S. Hristozov2, and D. Velev3 P. Zlateva et al.
  • 1Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia, Bulgaria
  • 2Institute of Robotics, Bulgarian Academy of Sciences, Sofia, Bulgaria
  • 3University of National and World Economy, Sofia, Bulgaria

Keywords: Fuzzy logic model, Drones, Drone capability, Risk assessment, Disaster risk management

Abstract. The paper proposes a fuzzy logic approach for drone capability analysis on disaster risk assessment. In particular, a fuzzy logic model is designed as a hierarchical system with several inputs and one output. The system inputs corresponds to the linguistic variables, describing the of levels of the external and internal input factors, which determine the capability levels of analysed drone in respect to disaster risk assessment. As external input factors are used, for example: disaster type (flood, landslide, wildfire); weather conditions (wind speed, fog, cloud cover); operational area (urban, mountain, plain), etc. As internal input factors are considered the drone characteristics such as drone type, flight performance (stall speed, turn radius, flight endurance), payload capabilities (camera resolution, accuracy, weight, sensors), etc. The fuzzy logic system output gives the level of the drone capability on disaster risk assessment in defined conditions. The model is designed in Matlab computer environment using Fuzzy Logic Toolbox. Several computer simulations are carried out to validate the proposed model. The designed fuzzy logic model is part of an information system for disaster risk management using drones, which is under development.