Addressing Human casualties of intense bushfires by utilising Intelligent Autonomous Unmanned Arial Vehicles

School of Engineering and Technology
Jahan Hassan
Ayub Bokani and Farzad Sanati


Increased intensity and frequency of natural disasters in recent years have caused great humanitarian, economic, and environmental catastrophes worldwide. Australia among several other countries continues to experience unprecedented destruction from bushfires with increased intensity, length, and frequency. Traditional methods and tools used in the current disaster management process are deemed insufficient in the face of such intense natural disasters. Many firefighters and civilians lose their lives because of the unpredictability of rapidly moving bushfires. The use of intelligent Unmanned Aerial Vehicle (UAV) can significantly improve the survival chance of humans in proximity to the firefront in the event of a large-scale bushfire. This research project aligns with CQUniversity's "Smart Systems" research strength, and it aims to investigate an innovative mechanism that can prevent and effectively respond to bushfires using Intelligent Autonomous UAVs. Depending on the approach taken by the individual RHD candidate, the use of Machine Learning and neural network techniques can present a significantly precise and predictive navigation system that can predict the velocity and trajectory of bushfire front lines at the micro level to assist/advise ground firefighting crow and civilians within the perceived danger area to take safer and more effective course of actions when needed.

Information and Computing Sciences| Engineering| Technology
Pridictive UAV Navigation, Machine Learning, Long Range Mesh Networks
August 2020 or later by negotiation
Sydney| Townsville

Project contacts