Intel Corporation

Hoang Tran Van

Addicam V Sanjay

Michael C Wu

Siew Wen Chin

Ravindra V Narkhede

Fatema Adenwala

Kalpana A Algotar

Daniel Gutwein

Neethu Elizabeth Simon

Systems, apparatuses, and methods include technology that generates synthesized sensors that synthesize operations of a first plurality of sensors using independent variables, such as sensors, as first inputs, where the first plurality of sensors is to sense conditions of operations of a system as the system executes a process based on a first input, and further where the conditions are stored as a first output. The technology generates a second output based on the synthesized sensors and the first input and detects whether one or more of a degradation and an anomalous state exists based on a comparison of the first output to the second output.

Detection of degradation or an anomalous state across heterogenous internet-of-things devices using synthesized sensors

In various embodiments, an RFID Antenna/Tag Location Configuration device (RLC) may facilitate placement of one or more RFID antennas in a physical space. The RLC may collect RFID data from tags determine which of the RFID antennas need to be relocated. The RLC may determine, based on collected RFID data, whether each antenna is a dominant antenna and/or has a substantial read rate. If an antenna is not dominant and/or does not exhibit a substantial read-rate, the RLC ma indicate that the antenna should be relocated. The RLC may also be configured to filter collected RFID data prior to using the data for determination of antennas. The RLC may also determine, using the RFID antennas, a physical location of RFID tags in the physical space using detected signal strength for RFID tags. Additional embodiments may be described and/or claimed.

RFID antenna re-location and/or RFID location

Certain embodiments may include a method, system, apparatus, and/or machine accessible storage medium to: obtain baseline data associated with a device, wherein the baseline data comprises an indication of an expected performance of the device during healthy operation; obtain status data associated with the device, wherein the status data is obtained based on operational information monitored by a sensor; compute delta data based on a delta between the status data and the baseline data; compute a standard deviation of the delta data; compute a plurality of standard deviation bands based on the standard deviation of the delta data; compute a statistical distribution of the delta data based on the plurality of standard deviation bands; and detect a fault in the device based on the statistical distribution of the delta data.

Fault detection using data distribution characteristics

Techniques for monitoring the health of a device comprising a motor or generator are described. An apparatus to monitor the health of the device includes a plurality of sensors to detect root-mean-square (RMS) current values for a plurality of stator windings of the device. The apparatus also includes a processor to receive the RMS current values from the plurality of sensors and compute a fault indicator based on the RMS current values. The fault indicator represents a level of current imbalance between the plurality of stator windings due to winding faults.

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Phoenix, AZ, United States of America

Hoang Tran Van