What?

An anomaly is  a deviation from what is standard, normal, or expected. Simply put: anything that goes wrong or that is unusual. To accurately detect anomalies, you need to know how the asset should behave every moment in time, in any context (e.g. a cold sunny day with a certain wind speed and direction combined with a certain production phase that is running).

How we do it

Eneos builds incredibly accurate models, with limited amounts of data!
‍(No need for incredibly dense metering, configuring loads of rules or complex  "manual" models such as BIM models)
Just send us the main metering data on the aspect you want to model (e.g. Energy consumption, Steam usage, production efficiency, etc.). Our proprietary AI technology will collect and derive context from it and create the best possible model, fully automatic.
This model mimics the normal behavior of a building/process/site, considering the interfering variables.
On top of that we have built a statistical layer that analyses if a deviation is probably just a glitch or an actual anomaly. This way you only get notified when needed, limiting distractions by false alarms.
Overall our system is more accurate & way more economical than a big team of data scientists, is scalable by design = fast deployment, requires almost no configuration and will give you ONE overview off all of your assets.
And as with everything we do: fully integrable with your existing EMS/data collection platform. No need to change platforms

Accuracy of model

The more accurate the model is, the better it can mimic the normal behavior. This way it will also better detects deviations from it. Our accurate models avoid the following:

• Lots of False Positives: There are a lot of alarms for e.g. Leakages, but often there is nothing wrong. This creates overhead and people start ignoring notifications.
• Missing Real Abnormalities: Anomaly remains detected - results in losses and damage