Forest & Rangeland Fire Prevention

Detect smoke plumes in their first minutes across forests, grasslands and protected areas.

Smart Fire PreventionCity & Environment

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Pain points

The challenge

Sound familiar? These are the problems our customers bring to us every week.

Fire lookouts and satellite passes miss the first, most controllable minutes.

By the time a fire is reported it has already spread.

Vast areas simply cannot be watched by people.

Solution overview

How this solution works

Detect smoke plumes in their first minutes across forests, grasslands and protected areas.

Every XCAN AI Box runs its algorithms on the edge, which means detection continues even when the network does not. Existing cameras are reused, alerts are verified with snapshots and clips, and all events land in one management console.

Forest & Rangeland Fire Prevention - AI video analytics deployment

How it works

Deployment in four steps

From the cameras you already own to a fully monitored site - typically inside one week.

Watch from high points

Cameras on towers and masts cover large areas.

Detect smoke early

Smoke and flame detection raises an alarm on the first visible plume.

Locate the fire

Overlay the alarm on a map so the response team heads to the right spot.

Protect people too

Intrusion detection covers restricted protected zones.

Algorithm library

AI algorithms used in this solution

Each algorithm can be enabled per channel, per schedule, with its own sensitivity and alarm rule.

Forest / Rangeland SmokeFire / Smoke DetectionIntrusion DetectionVehicle Detection & CountingLoitering Detection

Browse the full algorithm library

Hardware

Recommended hardware

Right-sized appliance and software for sites like this.

8-CH

XCORE-8

Doubles the channel count and algorithm slots of the XCORE-4 while keeping the same fanless, maintenance-free design. The most popular choice for community gates, campuses and small factories.

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16-CH

XCORE-16

Handles 16 cameras with per-channel algorithm profiles. Supports RAID-less dual storage, multi-user roles and open API push to third-party platforms.

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Benefits

What you get

Outcomes our customers measure after deployment.

The first few minutes, when a fire is still small, become actionable.
Enormous areas covered by a handful of AI-enabled cameras.
Clear evidence for investigation of suspected arson.

Use cases

Typical deployment scenarios

This solution is field-proven in the following environments.

Fire towerForest edgeGrasslandProtected reserveVillage boundaryPower line corridorTourist trail

FAQ

Frequently asked questions

How far can it detect smoke?

Detection range depends on visibility and camera optics; with a long-lens camera on a tower, plumes can be detected several kilometres away.

Does it work in fog or haze?

Fog reduces range. Thermal cameras are recommended alongside visible-light cameras to maintain detection when visibility is poor.

Case studies

Where this is deployed

Recent projects built on this class of solution.

City Management

A city district automates illegal-dumping and waste-overflow detection

Over 400 existing cameras were connected to XCORE-32 boxes, generating evidence packages that cut enforcement response time dramatically.

400cameras

-60%dispatch time

Read the case study

Tourism

A scenic area manages peak-season crowding with real-time visitor data

Gate and path counting on XCORE-16 boxes feeds a live capacity dashboard, triggering one-way routing before paths and viewpoints become unsafe.

1.2Mvisitors / year

-45%crowding incidents