In the last couple of years, it appears to have somewhat belatedly dawned on California legislators and firefighting officials that investing in early detection and quick response technology is cheaper than sending massive teams of firefighters to wildland fires that have grown to unmanageable proportions due to delayed detection and response. California’s wildfire detection and fire scene management technology these days uses artificial intelligence, multi-sensory ground networks, infra-red night vision, pattern recognition, and “predictive utility monitoring” to prevent fires and/or get on them before they get too big. The “ALERTCalifornia Platform” is a public-private partnership between UC San Diego, Cal-Fire, and DigitalPath networks which now includes over 1,100 pan-tilt-zoom cameras statewide. Factoring in weather and condition analysis of humidity, wind speed and direction, and vegetation dryness, the system can spot smoke and heat signatures in real time and generate alerts. When an “anomaly” is detected the system automatically texts real-time alerts with an accompanying “certainty score” to dispatch centers which are said to be earlier than human emergency calls more than 30% of the time. Some counties (apparently not Mendo yet) use ultra-sensitive computerized air-quality sensors that flag tiny chemical changes that may signal smoke in the vicinity before a smoke plume is visible to cameras. Fire crews also deploy specialized drones equipped with advanced thermal sensors that can see through heavy smoke, night and day, to map hidden hot spots and fire boundaries as fires burn. Specialized fireball-equipped drones have also been used to precisely set backfires in areas human firefighters are unable to access. As useful as drones are, however, drones are not allowed to be in the air space above an active fire scene because they pose a risk to aircraft. PG&E now operates centralized, continuous monitoring centers that take in millions of power grid sensor data