Blended iot device health index

A system comprising:

• a sensor configured to measure a physical condition;
• a device operable to affect the physical condition measured by the sensor;
• and
• one or more processors and one or more non-transitory computer-readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• operating the device to affect the physical condition measured by the sensor during a training phase;
• in response to the sensor collecting a minimum number of data values during the training phase, transitioning the device from the training phase to an operating phase and establishing an anomaly count baseline comprising an anomaly count limit using the data values collected by the sensor during the training phase;
• operating the device to affect the physical condition measured by the sensor during the operating phase comprising a time period over which anomalies for the device are counted, wherein an anomaly comprises sensor data from the sensor exceeding a statistical outlier limit and an anomaly count for the device comprises a number of anomalies within the sensor data during the time period;
• and
• performing an automated action based on whether the anomaly count for the device exceeds the anomaly count limit during the operating phase.

One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• operating a device to affect a physical condition measured by a sensor during a training phase;
• in response to the sensor collecting a minimum number of data values during the training phase, transitioning the device from the training phase to an operating phase and establishing an anomaly count baseline comprising an anomaly count limit using the data values collected by the sensor during the training phase;
• operating the device to affect the physical condition measured by the sensor during the operating phase comprising a time period over which anomalies for the device are counted, wherein an anomaly comprises sensor data from the sensor exceeding a statistical outlier limit and an anomaly count for the device comprises a number of anomalies within the sensor data during the time period;
• and
• performing an automated action based on whether the anomaly count for the device exceeds the anomaly count limit during the operating phase.