A mathematical model for balancing safety and economy of UAVs in forest firefighting

Zixin Peng; Genglin Zhu; Mu Li; Ruifeng Zeng; Sibo Cheng; Kaisheng Wang

doi:10.1117/12.2638930

17 May 2022 A mathematical model for balancing safety and economy of UAVs in forest firefighting

Zixin Peng, Genglin Zhu, Mu Li, Ruifeng Zeng, Sibo Cheng, Kaisheng Wang

Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 1225936 (2022) https://doi.org/10.1117/12.2638930
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, 2022, Kunming, China

Abstract

Forest fires have a tremendous negative impact on the global ecology and the national economy. Advances in information machine technology have paved the way for the use of Unmanned Aerial Vehicles (UAVs) to fight forest fires, including monitoring fires and expanding signal propagation. However, in practical applications, we must consider the characteristics of UAVs such as monitoring range and the difficulties in balancing safety and economics. We take the 2019-2020 bushfires in Victoria and New South Wales as a case study and explore how best to combine two types of UAVs, SSA drones and radio repeater drones, to balance safety and cost-effectiveness. In this paper, we first employ the particle swarm algorithm to reasonably schedule the minimum number of SSA drones patrolling the sky while maximizing their surveillance area for the fire area. Then, we propose a Topology Spanning Tree (TST) algorithm to determine the locations of Emergency Operations Centers (EOCs) and Radio Repeater drones and the minimum number required. Then, we use the Ant Colony Algorithm to find the shortest path of the drones from the EOCs to the designated patrol location to reduce the loss of their flight power. Finally, we set up a multiple regression equation to find the minimum cost using the size and frequency of fire events as parameters.

Citation Download Citation

Zixin Peng, Genglin Zhu, Mu Li, Ruifeng Zeng, Sibo Cheng, and Kaisheng Wang "A mathematical model for balancing safety and economy of UAVs in forest firefighting", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 1225936 (17 May 2022); https://doi.org/10.1117/12.2638930

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Mathematical modeling

Unmanned aerial vehicles

Particles

Relays

Safety

Data modeling

Evolutionary algorithms

Show All Keywords

Keywords/Phrases

Search In:

Publication Years