Robotics Cats AI Wildfire Detection

Novico Engineering delivers Robotics Cats AI wildfire detection in Malaysia. The LookOut platform uses wide-area cameras and computer vision to watch a landscape continuously, so early smoke is identified and escalated before it becomes an incident.

Robotics Cats (RoboticsCats) develops the LookOut detection platform; Novico Engineering delivers it in Malaysia.

Robotics Cats LookOut pan-tilt camera mounted in the field, monitoring hillside terrain around a substation and wind farm

Robotics Cats LookOut pan-tilt detection camera installed in the field. Image: Robotics Cats.

Detection time decides the outcome.

Across plantations, forestry operations, large estates, utilities and remote infrastructure, fire risk is concentrated in places nobody is standing. Detection usually depends on someone happening to see smoke, and by then the response is already behind.

Continuous wide-area monitoring changes that. Cameras observe the landscape without interruption, and computer vision models analyse the imagery for early smoke or fire signatures. When a likely event is identified, an alert is raised with the location and camera view so a response team can verify and act.

Novico is not the technology developer. We work with Robotics Cats and deliver this as a specialist offering — site assessment, deployment planning and operational integration.

WHERE IT APPLIES?

  • Plantations and agricultural estates

  • Forestry operations and managed woodland

  • Utilities and transmission corridors

  • Remote infrastructure and industrial sites

  • Large landholdings with limited on-site presence

How AI Wildfire Detection Works?

3 Steps - Monitor. Detect. Alert.

  1. Monitor the landscape

    Fixed wide-area cameras sweep the landholding continuously, covering terrain that nobody is standing in.

  2. Detect the smoke signature

    Computer vision models analyse the imagery for the visual signature of early smoke or flame, filtering routine haze, cloud and dust.

  3. Issue the alert

    A likely event is escalated with the camera view and location, so a response team can verify and act on it.

Our AI Wildfire Detection Deployment Process

Assess. Pilot. Deploy. Operate.

  1. Site assessment

    Understand the landholding, the terrain, the risk areas and the existing response procedure.

  2. Pilot deployment

    Deploy camera coverage over a defined zone and evaluate detection behaviour in real conditions.

  3. Scale

    Extend coverage across the priority areas identified in the pilot, with power and connectivity planned per location.

  4. Operate

    Integrate alerting into the client's response workflow so a detection reaches the people who can act on it.

The product, and what it sees.

Robotics Cats LookOut wildfire detection camera unit in its weatherproof housing on a wall bracket

Robotics Cats LookOut camera unit — a weatherproof fixed camera that can be mounted on existing masts, towers and building structures.

Robotics Cats LookOut camera image with an early smoke plume marked by a red detection bounding box and confidence score

A live LookOut frame with early smoke marked by a bounding box and confidence score.

How the Robotics Cats system is put together.

Robotics Cats publishes wide-area coverage at 15 km or more per camera and detection of wildfire inception within around ten minutes, alongside live situational information and microclimate awareness. Product tiers are LookOut Standard, LookOut Premium and LookOut GeoTrace, which adds wildfire location; FireBird Guard, adding acoustic bird deterrence, is at pilot stage.

Robotics Cats states it is used by customers in 14 countries across government, forestry, energy, homeowner associations and NGOs. These are the technology partner's own figures, not Novico project results.

INPUT

  • Cameras or an edge computer send JPG images to the detection API

  • Recommended image size 1920 x 1080 pixels

  • Hardware agnostic — existing surveillance cameras can be used

PROCESSING

  • Machine learning classification model looks for early-stage wildfire in each image

  • Configurable minimum confidence score

  • Configurable bounding box range

  • Scheduled background masking to suppress known false sources

OUTPUT

  • Real-time detection alerts by email, Pushover and Telegram

  • Customer-defined alert contact list and portal access

  • Integration through API, mobile app, desktop or VMS

Wildfire detection questions

  • Wide-area cameras continuously observe a landscape. Computer vision models analyse the imagery for early smoke and fire signatures, and raise an alert with the camera view and location when a likely event is identified.

  • No. Robotics Cats develops the detection technology. Novico offers it in Malaysia as a specialist technology, and handles the engineering, siting and deployment considerations around it.

  • Plantations, forestry operations, large estates, remote infrastructure, utilities, large land holdings, industrial sites adjacent to vegetation, and relevant government or environmental organisations.

  • The alert is delivered to the nominated responders with the associated camera imagery, so the event can be verified visually before a response is mobilised.

  • The usual starting point is a pilot deployment on a defined area, so coverage, siting and alerting can be assessed against your own operational conditions.

Where to next

Considering wildfire detection for your site?

A pilot deployment is the practical way to evaluate this. Tell us about the landholding and we will explain how we would approach it.

Discuss a Project 🡢