Optimization of Drone Quantity Based on Empirical Analysis in Bushfire Extinguishment. Issue 2 (June 2021)
- Record Type:
- Journal Article
- Title:
- Optimization of Drone Quantity Based on Empirical Analysis in Bushfire Extinguishment. Issue 2 (June 2021)
- Main Title:
- Optimization of Drone Quantity Based on Empirical Analysis in Bushfire Extinguishment
- Authors:
- Zhou, Zilong
Lin, Fu
Gong, Xinyi - Abstract:
- Abstract: With the deterioration in the environment, extreme weather is more likely to occur. The wildfire is becoming severer in turns of frequency and magnitude, causing disastrous damage to our fragile ecosystem. In this paper, we purpose a model to identify the optimal number of drones in case of any potential threat posed by bushfire in Victoria, Australia. In this paper, we use satellite data from space agencies such as NASA and the European Space Agency to determine the initial conditions and parameters of the model. including land cover, topography, traffic development, potential reinforcements nearby, distance to water and historical wildfires. We extract the data of several modes and determine the coefficients that affect the forest-mass. According to our simulation results, the optimal expected number of SSA UAV and relay UAV is 53 and 85 respectively.
- Is Part Of:
- Journal of physics. Volume 1952:Issue 2(2021)
- Journal:
- Journal of physics
- Issue:
- Volume 1952:Issue 2(2021)
- Issue Display:
- Volume 1952, Issue 2 (2021)
- Year:
- 2021
- Volume:
- 1952
- Issue:
- 2
- Issue Sort Value:
- 2021-1952-0002-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-06
- Subjects:
- UAV -- wildfire protection -- relay communication -- optimization
Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1952/2/022052 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
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British Library HMNTS - ELD Digital store - Ingest File:
- 17478.xml