[SENSE · CONTINUOUS FLARE MONITORING]

The state of every flare, inferred at the edge. In seconds.

The CarbonSense Flare Monitor watches every flare with LWIR thermal imaging, RGB vision and an acoustic proxy. It infers combustion state on the device and quantifies vented CH₄ from process data for confirmed venting events.

JOIN THE PILOTQualcomm AI Program for Innovators 2026
6inferred combustion states
8.7 Hzradiometric LWIR thermal
< 50 mstarget latency of the edge flame gate
100%of CH₄ mass calculated from SCADA flow
Bench validation with a digital twin · operators now being selected for the field pilot.
[COMBUSTION-STATE INFERENCE]

We call the state of the flame. And prove every number.

Sense is not a molecular methane sensor. It is combustion-state inference, with quantification that is defensible by design.

LIT · NORMALLIT · SMOKINGDEGRADEDFLAMEOUTVENTINGNO FLOW
Quantification rule
m = Q(Nm³/h) · h · x · 0.717

CH₄ mass quantified only during confirmed VENTING, using SCADA flow — never derived from smoke or opacity. Every event carries duration, thermal evidence and an auditable trail.

[FLEET DASHBOARD]

Your whole flare fleet, live, on one screen.

States, events, vented mass and device health — from onshore clusters to FPSOs.

app.carbonova.ai · Sense● live
12/14devices online
14flares · 7 sites
3active alerts
5,660 kgvented CH₄ (30d)
VENTINGCluster B — Flare 1Alfa SiteCH₄ 929.9 kg · ≈ 27.7 t CO₂e
LIT · SMOKINGF-102 — Process FlareDelta Refinery54k Nm³/d
LIT · NORMALHP FlareAtlântico FPSO181k Nm³/d
OFFLINEEP-3 — Cluster FlareSerra Alta Stationlast reading 7 h ago
Illustrative data from the demo environment.
[EDGE AI · HARDWARE]

Three signals. One verdict per frame.

Embedded INT8 models run on the device itself — no data link required to infer the state of the flame.

PRIMARY SENSOR
Radiometric LWIR thermal

160×120 @ 8.7 Hz. Thermal signature of the flame — the first gate of the flameout detector, with sun-glint and hot-surface rejection via FFT.

SECONDARY SENSOR
Co-located RGB vision

Three-class smoke classification (Ringelmann proxy 0/1/2), paired frame by frame with the thermal channel.

TERTIARY SENSOR
Acoustic flow proxy

Flow state from the sound signature — additional evidence to tell venting apart from no flow.

Edge Impulse → INT8 → QRB (Qualcomm) → OTA across the whole fleet · synthetic dataset generated by a digital twin, with rare events covered by design
[SENSE → CARBONOS]

Every event becomes auditable evidence.

Confirmed events flow into CarbonOS: vented mass enters the GHG inventory with full lineage in the Proof Engine, including duration, SCADA flow, thermal evidence and acknowledgement trail.

◆CH₄ mass per event → Scope 1 inventory
◆Audit-grade evidence trail (Proof Engine)
◆Alerts with triage, acknowledgement and resolution
◆Edge → cloud via AIoT Hub, with OTA model updates
CarbonSense Flare Monitor
↓
Confirmed event + m (kg CH₄)
↓
CarbonOS · Proof Engine · Inventory
[Frequently asked questions]

Carbonova Sense flare monitoring: frequently asked questions

Short answers on how Sense infers flare combustion state and records venting events. To learn about the pilot, book a demo.

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What is Carbonova Sense?

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Carbonova Sense is an edge AI system for flares, currently at pilot stage. On the device itself, it infers each flare’s combustion state (lit and normal, smoking, degraded, flameout, venting or no flow) from radiometric LWIR thermal imaging, RGB vision and an acoustic proxy. Vented CH₄ is quantified only for confirmed venting, from SCADA flow data. Sense does not measure methane in the air.

What problem does Carbonova Sense solve, and who is it for?

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Inventories usually assume flares stay lit and burn well, but airborne measurements across three US basins found that flares effectively destroyed only 91.1% of methane, against the 98% assumed (Plant et al., Science, 2022). Sense is for operators of flares in production, processing and refining: operations, HSE and emissions inventory teams that need to know when a flame went out and how much gas was vented in that window.

How does Carbonova Sense work, and what data does it use?

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Three signals reach the device: LWIR thermal imaging is the first gate of the flameout detector, the RGB camera classifies smoke into three classes, and the acoustic proxy helps tell venting apart from no flow. Embedded INT8 models give one verdict per frame without needing a data link. During confirmed venting, CH₄ mass comes from SCADA flow (m = Q · h · x · 0.717), never from smoke or opacity.

Which flaring rules matter for Carbonova Sense in the UK?

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Operators on the UK Continental Shelf need North Sea Transition Authority consent to flare or vent during production, and the NSTA expects zero routine flaring and venting by 2030, with new developments planned on that basis (NSTA). Sense infers each flare’s combustion state at the edge and logs flameouts and confirmed venting, with vented methane calculated from SCADA flow, giving operators an auditable record to set against their consents and emissions reports.

How does Carbonova Sense connect with CarbonOS and Build?

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Every confirmed event flows into CarbonOS with its duration, SCADA flow, thermal evidence and acknowledgement trail. The CH₄ mass enters the Carbon Intelligence Scope 1 inventory with full lineage in Proof Engine, and alerts go through triage, acknowledgement and resolution. The edge-to-cloud link runs through Build’s AIoT Hub, which also pushes over-the-air model updates to the whole fleet.

Does Carbonova Sense measure methane or detect leaks?

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No. Sense is not a methane sensor or a leak detector, and it does not measure methane in the air. It infers the flare’s combustion state and quantifies CH₄ only when it confirms venting, using the flow measured by SCADA and the methane fraction of the gas. Fugitive leaks from valves and flanges are out of scope, and an unlit flare with no flow is not counted as an emission event. That boundary is what makes each number defensible.

[PILOT PROGRAMME]

A few flares. Total evidence.

We are selecting operators for the CarbonSense Flare Monitor pilot — starting with sites that have critical flares and available process data. Developed within the Qualcomm AI Program for Innovators 2026.