Jill is building the future of infrastructure protection — where drones see in spectrums we can't, AI thinks at the edge, and wildfires are detected before they can spread.
An interactive simulation of drone-based sensing. Toggle between view modes to understand how LiDAR and hyperspectral imaging reveal what's invisible to the human eye.
Light Detection and Ranging creates precise 3D maps of terrain and structures by measuring how long laser pulses take to return. It sees through smoke and darkness.
Beyond RGB — capturing hundreds of wavelengths across the electromagnetic spectrum. It detects heat signatures, vegetation stress, and chemical changes invisible to our eyes.
Processing data on the drone itself, not in distant servers. Real-time detection with millisecond response times. The AI decides what matters before the data ever leaves the sky.
Identifying fires in their earliest stages — often before visible flames appear. Thermal anomalies, smoke particulates, and vegetation changes trigger alerts automatically.
Imagine a world where critical infrastructure — power grids, bridges, pipelines, forests — is continuously monitored by intelligent systems that detect threats before disasters strike.
A drone detects a thermal anomaly near a power line — elevated temperatures suggesting a potential fault or fire risk. The AI flags it instantly.
Edge computing processes LiDAR and hyperspectral data on-board. No cloud latency. The system cross-references vegetation density, wind patterns, and infrastructure proximity.
Alerts reach response teams within seconds, not hours. Precise GPS coordinates, severity assessment, and recommended actions — all before smoke is visible to the human eye.
What could have been a catastrophic wildfire becomes a managed incident. Power stays on. Communities stay safe. The grid stays resilient.
The best time to detect a wildfire is before it starts. The best infrastructure is the kind that protects itself.
— The future Jill is making real