Wildfire@Home
Personalized Immersive Training for Household Situation Awareness
Tianyi Xiao (ETH Zürich)
Yan Feng (TU Delft - Civil Engineering & Geosciences)
Suvodip Chakraborty (ETH Zürich)
Peter Kiefer (ETH Zürich)
Phoebe O. Toups Dugas (Monash University)
Martin Raubal (ETH Zürich)
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Abstract
As wildfires become increasingly frequent and severe worldwide, at-risk homeowners face greater responsibility in assessing the fire situation and making safety-critical decisions. This requires specific training in situational awareness (SA). However, the effectiveness of conventional wildfire response training (WRT) methods (e.g., videos, brochures) is limited, as they cannot replicate the unpredictability of wildfires nor provide real-world context. This research introduces Personalized Immersive Training (PIT), a novel paradigm designed to embed WRT in real-world contexts. We implemented PIT in Wildfire@Home, intending to increase homeowners' SA capabilities. Learners first use a desktop wildfire simulator to build mental models of how terrain, vegetation, and wind shape fire spread. Then, experience a realistic and immersive 3D rendering of the simulation in a VR wildfire visualizer. Learners can personalize the training scenario by uploading 3D models and geospatial data.
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