AI Solutions for Energy: Oil, Gas & Power Safety
An energy site already has more instrumentation than almost any other industrial environment — pressure, temperature, flow, vibration, gas concentration, thousands of tagged points streaming into a control room. What it usually does not have is anyone watching the twenty per cent of risk that shows up visually first: the contractor without a hard hat on the pipe rack, the haze at a flange before the gas detector reaches its threshold, the vehicle reversing into a bund wall, the person on the ground at the bottom of a stair.
AI solutions for energy close that gap without adding a sensor. The cameras are already mounted, the network is already there, and the footage is already being recorded and never reviewed. Adding on-device video analytics turns an existing recording system into an active detection layer — one that raises an event in seconds rather than providing evidence after the fact.
The Failure Modes That Repeat Across the Sector
Across upstream, midstream and downstream, the incidents that generate reports and downtime fall into a short list. PPE failures — missing hard hat, missing flame-resistant clothing, no gloves at a sampling point — remain the most common finding on every site audit, and they correlate with the injuries that follow. Hot work without a fire watch turns a routine grinding job into a plant emergency. Restricted-area entry by contractors who have not been briefed on that unit. Vehicle and plant interaction, which is where the serious injuries concentrate: a truck reversing in a live area, a forklift and a pedestrian in the same blind corner. Then housekeeping and leak precursors — a stain under a pump, vapour at a seal, a fire extinguisher that has been removed and not returned.
Each of these has a corresponding algorithm, and each is a detection problem rather than a judgement problem. That is the criterion worth applying when you evaluate any analytics claim: if a competent observer watching the same frame would unambiguously say “that is wrong”, a model can be trained to say it too, continuously, on every channel at once.
Upstream: Well Pads, Rigs and Remote Locations
Remote sites have a particular profile: few people, high consequence, connectivity that cannot be relied on, and no guard. Three things matter more here than anywhere else. The first is that detection has to run at the site, because a satellite or microwave backhaul that supports a historian cannot carry video, and a rule that depends on a round trip to a data centre simply stops working when the link degrades. The second is that the same cameras have to serve two masters — process observation during the day and security at night — which means time-windowed rules rather than permanently armed ones.
The third is that the incidents worth catching are unglamorous. A person entering the wellhead enclosure without authority is covered by intrusion detection. A tank farm approached from outside the fence is a job for perimeter security rules. A vapour release or a pool fire at a separator is what fire detection and smoke and fire detection exist for, and they will typically raise the alarm before a point gas detector at the perimeter does, because they see the event rather than waiting for the plume to arrive. Drips and staining at seals are the domain of leak detection.
Midstream: Pipelines, Compressors and Terminals
Compressor stations and pumping stations are unattended by design, which makes camera analytics the only continuous presence they have. The high-value detections are entry into a fenced compound, loitering at a valve site, a vehicle stopped alongside a right-of-way for longer than a patrol would accept, and ignition sources near a vent stack — the last of which is covered by smoking detection. Where third-party excavation threatens a line, the same intrusion rules that protect a compound can be pointed at the easement.
Terminals add a layer of vehicle and loading-bay risk: tanker positioning, wheel chocks, bonding connections, and the pedestrian who walks into a reversing path. This is where analytics composes with rather than replaces existing systems — the terminal’s access control and interlocks stay in charge of the process, and the cameras handle the parts no interlock can see.
Downstream and Power: Refineries, Plants and Substations
Refineries and petrochemical plants have the most mature safety instrumentation of any environment in the sector, and still record the same categories of finding year after year, because the failures are behavioural rather than instrumental. PPE compliance is the clearest case: it is measured by audit, which means it is measured rarely, and the number that gets reported is the number on the day of the audit. Continuous detection changes the denominator. Sites running hard hat detection and workwear and uniform detection on the cameras they already own get a real rate rather than a sampled one, and the pattern that emerges is usually specific to a location rather than a crew — one stairhead, one contractor route, one shift handover.
The other side of the same problem is equipment readiness: an extinguisher removed for a job and never returned, a shower or eyewash station blocked by a pallet, a fire door propped open. Fire equipment detection and clutter detection cover those, and they are the checks that audits reliably fail sites on. Substations and switching yards add a narrower but sharper set: unauthorised entry into a live compound, a person on the ground after a fall in an unmanned building, covered by fall detection. The broader plant-floor picture is described under factory safety, which shares most of the same detection set.
Why the Compute Has to Sit on the Site
Two arguments decide this, and neither is about preference. The first is bandwidth: a refinery with two hundred cameras cannot upload two hundred streams, and even where connectivity exists, the cost of egress exceeds the cost of the analytics many times over. The second is operational: detection that gates a response must survive a network outage, because network outages and incidents correlate. Processing on an appliance inside the network means video never leaves the site, detection keeps running when the backhaul fails, and latency is measured in milliseconds rather than round trips.
The practical shape is one appliance per site or per unit, scaled from 2 to 128 channels and 1 to 256 TOPS depending on how many streams and how many concurrent rules. Because the appliance is running the full 198+ algorithm library locally, adding a rule to an existing camera costs configuration rather than hardware — which is usually the detail that makes the economics work. The architectural trade-offs are set out in more detail in on-premise versus cloud analytics.
Compliance, Evidence and Deployment Reality
Detection is half the value; the other half is the record. Every event carries a timestamp, a camera, a clip and a classification, which turns an argument about whether something happened into a lookup. For sites working to process-safety regimes, that record supports the parts of an audit that are hardest to evidence: that controls were in place continuously, not on the day of the inspection. Sector standards bodies such as NFPA publish the fire and electrical codes most sites are assessed against, and ISO frames the management-system side; neither prescribes video analytics, and none of this is a substitute for the engineered safeguards that do the real work. What analytics adds is detection in the gaps between them.
On deployment itself, the honest answer is that most energy sites are harder to camera than a warehouse. Hazardous-area certification governs what can be mounted where, existing cameras are frequently pointed at process equipment rather than at people, and lighting at night is uneven. The workable approach is to start with the cameras you have, evaluate on a week of recorded footage, and only then decide which locations need a new device — in most projects that is a small fraction of the total. Sites with existing flammable-atmosphere rules will find the same constraint applies to the appliance, which sits in a safe-area rack rather than in the field. For the wider hazard and compliance picture, see our industrial and energy safety system guide.
Frequently Asked Questions
Can this run in hazardous areas?
The analytics appliance is installed in a safe-area rack or control room; it consumes ordinary IP streams over the existing network. Cameras in classified zones stay as they are, and if a new camera is needed in a hazardous location it is specified to the same certification as everything else already there.
What happens when the site loses its network connection?
Nothing changes for detection. Processing is on-device, so rules keep running and events keep being logged locally; only the notification to a remote control room is affected. When the link returns, the backlog synchronises. This is the main reason energy operators choose on-premise over cloud.
How do you keep false alarms down on a site with steam, flare glare and moving plant?
By region and by window, mostly. Steam vents, flare glow and rotating equipment are excluded from detection regions during commissioning, and rules that would fire on them are time-windowed or re-sited. We tune against a week of your footage before any rule goes live, and alert volume is reviewed again after the first fortnight.
Do we have to replace existing cameras or add a cloud subscription?
No on both counts. The platform runs on your current streams, from 2 to 128 channels and 1 to 256 TOPS on one appliance, with no per-camera licence and no video leaving the site. New cameras are only needed where a risk area has no coverage at all today.
Tell Us Your Scenario
Energy sites differ more from each other than the sector’s standards suggest, and the difference between a deployment that holds up and one that gets switched off is usually a week of configuration against real footage. Send us your camera layout, your network constraints and the incidents you are trying to prevent, and we will tell you which of the 198+ algorithms fit and what accuracy to expect on your own video. Tell Us Your Scenario — or start with a Starter Kit preloaded with tested configurations, running on your cameras in a single afternoon.