Electrical Sensor Adds Edge Computing Capabilities

The EnertivTwo, a circuit-level electrical demand sensor developed for commercial applications in high-rise and industrial buildings, mounts beside breaker boxes and uses split-core current transformers to monitor up to 42 circuits inside the panel. In addition to continuously uploading data to the cloud, the sensor has been upgraded to perform on-site “edge” computations. This enables detection of sub-second anomalies that were previously impossible to identify due to networking limitations.


Data anomalies are utilized by building operators and engineers to detect and predict equipment malfunctions before critical failures occur. Shifting the analysis from the cloud to the edge expands the range of malfunctions that can be detected, which is critical for operating newer smart buildings and older assets.


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Edge computing capabilities include pre-programmed anomaly detection as well as unsupervised algorithms that leverage machine learning algorithms to identify deviations from normal operations such as a phase imbalance or equipment short cycling. The sensor has been developed to meet the needs of commercial assets including installations in under two hours, no rewiring or power shutdown required, and, reportedly, the lowest cost per end point of any electrical demand sensor on the market. Features include:


Service Type

  • Single Phase
  • 3 Phase – 4 Wire (WYE)


Measurement Type

  • Current (A)
  • Voltage (V)
  • Power Factor
  • Frequency (Hz)
  • Power (kW, kVA, kVAR)


Measurement Range

  • 0 to 1,000A
  • 100-300VAC Line-to-Neutral


Input Channels

  • 42


Sampling Frequency

  • 500Hz


Update Rate

  • <1s


Measurement Accuracy

  • ±1% at full range



  • Three months of Offline Data Storage


For more insights, visit Enertiv.


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