A
system and method for wildfire detection, monitoring, and consequence modeling integrate digital cameras with
artificial intelligence to identify, track, and predict
fire behavior. The
system processes camera imagery,
satellite data, environmental inputs, aircraft
telemetry, and
contextual information to detect ignition points, triangulate fire locations, and model projected
fire spread. A
fire propagation engine generates maps, graphs, and consequence estimates, including burned area, affected infrastructure,
population exposure, and financial loss. Alerts are triggered based on detection and modeled
impact, with filters to suppress false positives, merge repeated detections, and escalate based on user-defined risk thresholds. The
system includes tools for managing prescribed fires, tracking
smoke-only detections, and customizing alert logic by geography, asset proximity, or
scenario. External datasets may be ingested via API or file upload to support consequence scoring and operational prioritization. Users may run simulations, analyze historical conditions, and export results for planning, response coordination, or regulatory reporting.