Virtual sensors

A Virtual sensor is like a digital twin that can replace or complement a physical sensor. With Edge Machine Learning you can learn individually onboard the connected device and save cost on expensive or redundant sensors. The power of virtual sensor lies in the fact that the physical sensor used by the virtual sensor may be heterogeneous. A virtual sensor calculates a value, based on multiple input variables, that is a replacement or a representation of a sensor value. With virtual sensors that use machine learning it is possible to learn complex correlations and predict values. The suitability of virtual sensors when;

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• Maintaining physical sensor is expensive

• Far from work station

• Assets that cannot be calculated by physical sensor

• Located at hostile environment or hazardous zone

• Costly implementation

 

Virtual sensor is very important element to solve number of different problems such as real-time prediction, system back-up, mitigation plan readiness, fault diagnosis analysis and more. This innovative data-driven approach offers a new and effective way of obtaining accurate readings along the entire processing chain without installing expensive hardware. We build a mathematical model that learns every detail and every interaction of a given process on the basis of a large number of stored historical measurements. A virtual sensor is a piece of software that calculates a target parameter based on input data and help process engineers to improve process control substantially. We have provided virtual sensor solutions to many establishment and the numbers keep growing every year.

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