Automated Behavior Labeling for IIoT Data

Abstract

We present an automated data analysis tool for IIoT applications that discovers process behavior patterns in sensor data. It takes time-varying sensor data from reference production cycles and performs clustering on summary statistic feature vectors derived from raw sensor data over configurable window sizes. It automatically labels the raw sensor data based on distinct behavior modes represented by the clusters. The tool wraps, as a web service deployed in a Docker container, the AI model represented by clusters/behavior modes discovered in the reference sensor data. We have successfully evaluated the tool over four industrial datasets. Demo video: https://www.youtube.com/watch?v=MhSnwPDnAh0.