Developer zachary.systems (mapldx on Hacker News) launched Signet in March 2026, an autonomous wildfire tracking system that continuously monitors the continental United States for wildfires without human intervention. Built in Go and using Gemini to orchestrate 23 tools, the system integrates NASA FIRMS thermal detections, GOES-19 satellite imagery, National Weather Service forecasts, and multiple geographic datasets to detect and assess fire activity.
Autonomous Orchestration Eliminates Human Intervention
Unlike traditional monitoring systems that require human operators to initiate investigations, Signet employs autonomous orchestration that "continuously triages NASA FIRMS detections, GOES-19 imagery, and follow-up investigations without waiting for a human to initiate each step," according to the developer. The system uses Gemini to orchestrate 23 tools across weather, terrain, imagery, and incident tracking to decide which weak detections merit investigation, what context to pull next, and how to synthesize noisy evidence into structured assessments.
Integration of Multiple Data Sources and Geographic Datasets
The developer explained the technical architecture: "All the data already exists: NASA FIRMS thermal detections, GOES-19 imagery, NWS forecasts, LANDFIRE fuel models, USGS elevation, Census population data, OpenStreetMap. The problem is it arrives from different sources on different cadences in different formats." Most of the system consists of deterministic data plumbing for ingestion, spatial indexing, and deduplication, with Gemini handling the intelligent decision-making layer where clean rules break down.
Falsifiable Predictions With Automated Validation
Signet records time-bounded predictions and scores them against later data, making falsifiable claims rather than just reporting detections. Structured databases contain raw FIRMS detections, interpreted GOES observations, weather inputs, predictions, and official cross-checks. The system provides active fire locations and intensities, high/critical severity classifications, fire persistence predictions, weather-based fire behavior analysis, and nearby exposure evaluation.
Free ZIP Code Alerts and Early Detection Capabilities
Users can receive free ZIP code-based alerts when notable fire activity is detected nearby. The system is already opening incidents from raw satellite detections and matching some to official NIFC reporting, demonstrating early detection capabilities beyond traditional monitoring systems.
Challenges and Limitations Acknowledged by Developer
The developer acknowledged current limitations: "But false positives, detection latency, and incident matching can still be rough." The system explicitly states it is "not a substitute for official emergency information," emphasizing its role as a supplementary monitoring tool rather than an authoritative source for emergency response.
Key Takeaways
- Signet autonomously monitors the continental US for wildfires using NASA FIRMS thermal detections, GOES-19 satellite imagery, and weather data without requiring human intervention to initiate investigations
- Built in Go, the system uses Gemini to orchestrate 23 tools across weather, terrain, imagery, and incident tracking for intelligent triage and assessment of fire detections
- The system records time-bounded predictions and validates them against later data, creating falsifiable claims rather than just reporting raw detections
- Users can receive free ZIP code-based alerts for nearby fire activity, with the system already matching detections to official NIFC incident reports
- The developer acknowledges challenges with false positives, detection latency, and incident matching, emphasizing the system is not a substitute for official emergency information