AI Thermal Anomaly Detection

Catch abnormal heat without drowning operators in noise

Industrial scenes are messy. Forklifts, hot work, sun, process heat, and normal equipment cycles can all look urgent if a system only watches fixed limits. AVIAN combines thermal imaging, RGB context, and baseline-aware detection so teams see the abnormal heat that deserves action.

Signal pipeline
  1. Thermal capture
  2. RGB context
  3. Baseline comparison
  4. Noise filter
  5. Anomaly alert

Why simple alarms fail

Heat problems rarely look clean in real facilities

A useful thermal system has to separate the heat that belongs in the process from the heat that signals failure, fire risk, or maintenance need. Otherwise operators learn to ignore alarms.

RGB camera monitoring sawmill equipment
Thermal camera monitoring sawmill equipment
Thermal view
RGB view

How AVIAN works

Thermal intelligence built for real industrial scenes

AVIAN combines thermal capture, RGB context, zone-based monitoring, adaptive baselines, and smart alarm filtering so teams see useful anomalies instead of raw camera noise.

  1. Layer 01

    Thermal and RGB context

    Operators see the heat signature and the visible scene together, so a hotspot is tied to the asset, belt edge, pile, panel, or process area that needs attention.

  2. Layer 02

    Baseline-aware detection

    The system tracks normal thermal behavior for each monitored zone and flags sustained drift instead of relying only on a generic temperature limit.

  3. Layer 03

    Noise filtering

    AVIAN filters routine industrial triggers such as forklifts, loaders, welding sparks, and hot work so alerts stay focused on events that deserve a response.

“I can be anywhere in the mill, or even sitting at home”

I can be anywhere in the mill, or even sitting at home and get an alert from AVIAN and I know it’s time to act immediately.

“Condition-Based Thermal Monitoring at Sierra Pacific Mills”
John Brummel
John BrummelSierra Pacific IndustriesMaintenance Superintendent
“We can now adjust our machines in real time—without shutting them down”

Temperature changes become immediately visible with the AVIAN system, allowing us to react without delay. This kind of predictive maintenance greatly increases technical availability.

Johann Zingl
Johann ZinglRubner HolzindustrieProduction Manager
“I’d argue it’s probably one of the best technologies as far as fire safety is concerned”

We had a gearbox that was overheating in our dust shed. Thanks to the alerts from AVIAN, we changed the oil in the gearbox and brought it back under normal operating conditions.

“From Pilot to Prevention: How Chinook Wood Products Uses AVIAN”
Peter Rempel
Peter RempelChinook Wood ProductsCOO

FAQ

Questions teams ask before they deploy AVIAN

Is AI thermal anomaly detection the same as predictive maintenance?

It is one practical input for predictive maintenance. AVIAN detects abnormal heat trends on monitored assets, then maintenance teams use that signal to inspect, schedule work, and prevent repeat failures before downtime or fire risk escalates.

Does AVIAN replace smoke detectors or flame detectors?

No. Smoke and flame detectors still matter for life safety and code-required fire detection. AVIAN watches an earlier stage of the event timeline: abnormal surface heat, friction, electrical faults, and process heat before smoke or flame appears.

Does anomaly detection require a new control system?

No. Operators can use AVIAN through a browser, phone, tablet, alerts, and reports. Sites that want automated response can integrate alerts into existing controls, but the anomaly detection workflow does not require a new SCADA workstation.

What kinds of anomalies does AVIAN detect?

Common examples include hot bearings, dragging conveyor belts, overheated motors, loose electrical connections, dust extraction heat, battery and charger heat, and equipment that drifts away from its normal thermal baseline.