Univariate anomaly detection in a sensor network

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United States of America Patent

PATENT NO 11060885
APP PUB NO 20210095996A1
SERIAL NO

16587334

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Embodiments determine anomalies in sensor data generated by a sensor. Embodiments receive a first time window of clean sensor data generated by the sensor, the clean sensor data including anomaly free data, and determine if the clean sensor data includes a cyclic pattern. When the clean sensor data has a cyclic pattern, embodiments divide the first time window into a plurality of segments of equal length, where each equal length includes the cyclic pattern. Embodiments convert the first time window and each of the plurality of segments into corresponding curves using Kernel Density Estimation (“KDE”). For each of the plurality of segments, embodiments determine a Kullback-Leibler (“KL”) divergence value between corresponding curves of the segment and the first time window to generate a plurality of KL divergence values.

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ORACLE INTERNATIONAL CORPORATION500 ORACLE PARKWAY M/S 50P7 REDWOOD SHORES CA 94065

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Desai, Utkarsh Milind Bangalore, IN 12 44
Gvd, Karthik Bengaluru, IN 5 10
Krishnamurthy, Vijayalakshmi Sunnyvale, US 22 186
Udani, Goldee Bengaluru, IN 5 98

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