Fuel Alerting

AI-driven monitoring of forest-floor fuel moisture triggers real-time ignition alerts, enabling utilities to proactively mitigate wildfire risks around power infrastructure.

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How does it work?

Utilities lack timely visibility into forest-floor fuel moisture and early ignition events, hindering proactive wildfire prevention along critical infrastructure. Combining high-resolution geospatial data with AI analytics delivers continuous moisture mapping and instant ignition alerts, empowering utilities to respond faster and reduce outage and fire damages.

Continuous Moisture Mapping: High-resolution satellite and drone imagery feed AI models to estimate forest-floor fuel moisture across service areas. This continuous mapping identifies drying trends before ignition risk escalates.
Real-Time Ignition Alerts: Machine learning algorithms detect thermal anomalies and smoke signatures to send immediate ignition alerts. Utilities can dispatch crews or shut off power in minutes, limiting fire spread.
Integrated Risk Dashboard: A unified dashboard displays moisture levels, ignition hotspots, and predictive risk scores. Stakeholders gain a clear, actionable overview for decision-making and resource allocation.
Historic Trend Analysis: Time-series analysis of moisture and ignition data reveals seasonal and climate-driven risk patterns. Forecasting models leverage these insights to anticipate high-risk periods and plan maintenance.
Scalable Coverage: Cloud-based processing scales across thousands of square kilometers, handling varied terrain and vegetation types. This ensures consistent monitoring across entire utility service networks.
Seamless Platform Integration: APIs and webhooks enable easy integration with existing SCADA, GIS, and incident management systems. Automated workflows reduce manual data handling and accelerate response.

Frequently asked questions

Have a different question and can’t find the answer you’re looking for? Reach out to our support team by sending us an email and we’ll get back to you as soon as we can.

How does this solution compare to ground-based moisture sensors?: Geospatial analytics covers larger areas with higher spatial resolution than sparse ground sensors. Combining remote sensing with AI reduces maintenance costs and provides more comprehensive moisture assessments.
Why is real-time ignition alerting popular among utilities?: Utilities prioritize rapid detection to prevent wildfire escalation and asset damage. Instant alerts from AI-driven models improve response times compared to manual monitoring or periodic aerial surveys.
What are the limitations of using satellite imagery for fuel moisture estimation?: Cloud cover and revisit intervals can delay data availability and obscure certain areas. Integrating drone flights and ground observations helps fill gaps and maintain consistent monitoring.
Are there alternatives to AI-based geospatial analysis for wildfire risk?: Traditional methods rely on manual patrols, fixed sensors, or weather station proxies that offer limited spatial coverage. AI-driven geospatial models combine diverse data sources for more precise and scalable risk assessments.
Can this platform integrate with existing utility management systems?: Yes, the solution provides APIs and connectors for SCADA, GIS, and incident management tools. This integration streamlines data flow and automates alert-triggered workflows within current operations.
How do you ensure data accuracy compared to conventional methods?: AI models are trained on historical moisture and ignition events, validated against ground truth measurements and sensor networks. Continuous model retraining and multisource data fusion maintain high accuracy across terrain types.

Geospatial AI Platform

Intelligence

AI & foundation models

Deep-learning and foundation models turn raw imagery into ready-to-use insights, so you ship answers instead of training pipelines.

Experience

Conversational workflow

Ask questions in plain language and the platform responds with charts, visualizations, and next step suggestions.

Speed

GPU-accelerated cloud

Cloud-native architecture spins up on-demand GPU clusters that scale from a single scene to global archives—no manual ops, no bottlenecks.

Data

Any sensor, any format

Optical, SAR, drone, IoT, vector or raster—ingest, fuse, and analyze without conversion headaches.

Visualization

Insight you can see

Real-time 2D / 3D maps and export-ready plots make results clear for engineers, execs, and clients alike.

Boost your productivity. Experience Geospatial AI.

Turn satellite, drone, and sensor data into clear, real-time insights using powerful AI – no complex setup, just answers you can see and act on.

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