Year: 2026
Type: preprint
Abstract: In recent years, wildfires in British Columbia have been increasing in both severity and frequency.In 2023, 2245 wildfires burned 2 840 545 hectares, making it the worst wildfire season on record.Wildfires destroy ecosystems, force evacuations, and cause several health problems; these impacts are only growing, along with wildfire frequency.The main cause of wildfires is lightning, which happens mostly in remote regions, so early detection relies on chance observation or delayed satellite detection.[1][3] Climate change is the biggest culprit for the growing wildfire problem.Climate change causes droughts, heatwaves, and higher temperatures, creating favourable conditions for wildfires.The hotter, drier conditions make the ignition-to-growth time much shorter; now more than ever, early detection is essential to stopping wildfire escalation.[4]The core issue is not our fire response capacity; it's fast responses and coverage.[2]My project addresses this problem using both a physical robot and a simulation.The robot is a proof of concept for an autonomous, self-charging wildfire detector.In addition, the simulation is used to simulate communication between detectors in the case of a wildfire. Literature ReviewHuman detection methods, such as lookout towers, 911 reports, and aerial patrols, have important limits for early wildfire detection.British Columbia has about 60 million hectares of forest land, making full human coverage unrealistic across such a large and remote area.Studies of fire lookout towers also show that their visibility is often limited: in one analysis, tower visibility ranged from 41.18% upward, and when smoke was assumed to remain at ground level, no towers exceeded 70% visibility.This matters because early detection depends on seeing a fire quickly, and in remote forests, that is difficult to guarantee with human observation alone.[5]
DOI: 10.58445/rars.4047
Author: Benjamin Han
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
SDGs: Climate action, Life on land
Open Access status: green
OpenAlex ID: W7202355148