Pano AI pitches camera-based wildfire detection system to committee

Pano AI demonstrated a tower-mounted camera network and human-in-the-loop verification process Wednesday to help detect wildfires early and give incident commanders visual intelligence before crews arrive.

Mikaela Baker, government affairs manager, explained every Pano station includes two high-definition rotating cameras that stitch a panoramic view and feed an AI model trained on millions of images for day and night detection. "When any alerts come from those third-party sources, our analysts are then gonna use the panel stations to ground truth those reports," she said.

Pano's platform ingests satellite imagery and other third-party data, offers optical zoom (up to 30x) for confirmation, and pushes text and email alerts with map layers and lat/longs to onboarded dispatch centers and fire partners. Operators can mark controlled burns in the dispatch system to avoid unnecessary responses; Pano staff said they will still alert if they cannot verify a detection.

The company said it is a turnkey provider that selects sites, negotiates tower leases, hardwires power and internet where available and deploys solar/Starlink/satellite backup when needed. Pano offered a price point of about $50,000 per station per year (two cameras per station), and representatives said that cost model can be scaled and negotiated for government deployments.

Committee members asked about false alarms from oil-field flaring and nighttime heat signatures; Pano noted human analyst review and optical zoom tools reduce false positives. The committee did not authorize procurement but asked staff to include Pano's technical and cost details in follow-up materials.