Masters Theses

Doaa Rjoub

Abstract

“Millions of acres of forests are destroyed by wildfires every year, causing ecological, environmental, and economical losses. The recent wildfires in Australia and the Western U.S. smothered multiple states with more than fifty million acres charred by the blazes. The warmer and drier climate makes scientists expect increases in the severity and frequency of wildfires and the associated risks in the future. These inescapable crises highlight the urgent need for early detection and prevention of wildfires. This work proposed an energy management framework that integrated unmanned aerial vehicle (UAV) with air quality sensors for early wildfire detection and forest monitoring. An autonomous patrol solution that effectively detects wildfire events, while preserving the UAV battery for a larger area of coverage was developed. The UAV can send real-time data (e.g., sensor readings, thermal pictures, videos, etc) to nearby communications base stations (BSs) when a wildfire is detected. An optimization problem that minimized the total UAV’s consumed energy and satisfied a certain quality-of-service (QoS) data rate were formulated and solved. More specifically, this study optimized the flight track of a UAV and the transmit power between the UAV and BSs. Finally, selected simulation results that illustrate the advantages of the proposed model were proposed”--Abstract, page iii.

Advisor(s)

Wang, Yang

Committee Member(s)

Xu, Guang
Zawodniok, Maciej Jan, 1975-

Department(s)

Civil, Architectural and Environmental Engineering

Degree Name

M.S. in Civil Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2021

Pagination

xii, 54 pages

Note about bibliography

Includes bibliographic references (pages 49-53).

Rights

© 2021 Doaa Rjoub, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 11919

Electronic OCLC #

1286686994

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