Abstract: 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.

Abstract: System and method for collection, control and display of cameras and images. Software may direct the cameras to targeted images automatically or manually. Artificial Intelligence (AI) may be used to identify targets and automatically direct one or more cameras to focus on a target. Images taken by one or more cameras may then be stored and displayed for later viewing or live streamed. AI may be used to analyze images (Hits) to (i) determine if such Hits are objects of interest; (ii) determine if the Hits are related to an existing Incident; (iii) if determining a Hit is related to an Incident, create a new Filter and associating the new Filter with the Incident; and (iv) if determining the Hit is unrelated to an Incident, create a new Filter, associate the Hit with the Filter and use such information to train the artificial intelligence.

Abstract: System and method for collection, control and display of cameras and images. Software may direct the cameras to targeted images automatically or manually. Artificial Intelligence (AI) may be used to identify targets and automatically direct one or more cameras to focus on a target. Images taken by one or more cameras may then be stored and displayed for later viewing or live streamed. AI may be used to analyze images (Hits) to (i) determine if such Hits are objects of interest; (ii) determine if the Hits are related to an existing Incident; (iii) if determining a Hit is related to an Incident, create a new Filter and associating the new Filter with the Incident; and (iv) if determining the Hit is unrelated to an Incident, create a new Filter, associate the Hit with the Filter and use such information to train the artificial intelligence.

Abstract: System and method for collection, control and display of cameras and images. Software may direct the cameras to targeted images automatically or manually. Artificial Intelligence (AI) may be used to identify targets and automatically direct one or more cameras to focus on a target. Images taken by one or more cameras may then be stored and displayed for later viewing or live streamed. Images may be aggregated to create up to a three hundred sixty-degree (360) view. Images may be conventional, thermal or infrared. Image parameters, such as sharpness and gain, may be adjusted in real-time at the camera level or during post processing on merged/panorama images to provide a consistent merged image for the end user. One or more cameras may be controlled by clicking on an image, including the generated panoramic 360 image, or a map overlaid with images and other data. Three dimensional (3D) models may be created by the software from the images taken by the cameras.