A theoretical framework for improved fire suppression by linking management models with smart early fire detection and suppression technologies

doi:10.1007/s11676-024-01737-3

Abstract

Abstract:

Bushfires are devastating to forest managers, owners, residents, and the natural environment. Recent technological advances indicate a potential for faster response times in terms of detecting and suppressing fires. However, to date, all these technologies have been applied in isolation. This paper introduces the latest fire detection and suppression technologies from ground to space. An operations research method was used to assemble these technologies into a theoretical framework for fire detection and suppression. The framework harnesses the advantages of satellite-based, drone, sensor, and human reporting technologies as well as image processing and artificial intelligence machine learning. The study concludes that, if a system is designed to maximise the use of available technologies and carefully adopts them through complementary arrangements, a fire detection and resource suppression system can achieve the ultimate aim: to reduce the risk of fire hazards and the damage they may cause.

Key words: Forest fire, Resource suppression, Smart fire detection and suppression system, Forest fire management, Holistic system

Li Meng, Jim O’Hehir, Jing Gao, Stefan Peters, Anthony Hay. A theoretical framework for improved fire suppression by linking management models with smart early fire detection and suppression technologies[J]. JOURNAL OF FORESTRY RESEARCH, 2024, 35(1): 86-.

Li Meng, Jim O’Hehir, Jing Gao, Stefan Peters, Anthony Hay. [J]. 林业研究(英文版), 2024, 35(1): 86-.

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