Automated Forest Fire Detection and Suppression Framework

Lead researcher: Dr Li Meng

The economy of the Green Triangle region is highly dependent on the forest industry and fire is the major risk. Early detection and successful suppression operations are critical to minimising loss due to fire impact on plantations, agriculture and local communities. This project examined the feasibility of emerging technology to enhance and automate fire detection and suppression in the Green Triangle region. Key benefits from the project include:

• Review of contemporary fire detection methods, fleet dispatch travel model and fire risk management model.
• Discussion of fire management factors from an operations research point of view, including fire management methods, technology systems and strategic planning.
• Analysis of results of current fire risk management modelling and camera tower utilisation technology applied in the Green Triangle area.
• Benchmarking of current detection and suppression system performance against potential camera and remote sensing systems.
• Development of a conceptual framework for an integrated smart fire suppression system including a GIS platform, a fire risk management model and a combined technology for a fire detection reporting system.
• Opportunity to better integrate the detection and suppression activities using the outputs from this project including tailoring suppression response to the modelled risks of potential fires.

Our team:  Li Meng, Jim O'Hehir, Stefan Peters, Jing Gao, Euan Ferguson (Euan Ferguson Pty Ltd), Anthony Hay (ESK Mapping & GIS), Owen Salkin (Natural Systems Analytics Pty Ltd), Greg Saunder (Forest Owners Conference)