FireGuard Capsule™ — From concept to working prototype
FireGuard Capsule™ started with a simple question: how can we detect wildfires earlier and give people more time to respond?
Since then, we have built the main software and intelligence layers of the system, including:
• Flutter mobile application • FastAPI backend and database • Real-time telemetry and alert processing • AI-based fire verification and environmental fire-risk assessment • NASA fire intelligence integration • GPS and GIS-based fire information • FireGuard AI Assistant with voice interaction • ESP32-based hardware and telemetry architecture
We also developed and evaluated a machine-learning pipeline using fire and environmental data. The current system is designed to clearly separate tested AI results from future physical-hardware testing.
The next stage is physical hardware integration, controlled testing and eventually field validation.
FireGuard Capsule™ is being developed with one goal: detect earlier, provide better information and give people more time to act.
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