Characterization of Event-Based Sampling Encoders for Industrial Internet of Things Using Input–Output Mutual Information

Abstract

The emergence of Industry 4.0 has resulted in a rapid increase in the demand for bandwidth due to the proliferation of the industrial Internet of Things (IIoT). Increased utilization of the network also gives rise to undesirable consequences such as high latency and increased likelihood of data loss through packet drops. Encoding inputs using event-based sampling is a potential solution for decreasing network traffic generated when continuous input variables are sampled. The problem addressed by this article is the fact that currently there is no effective method for comparing different encoders. The resulting contribution is the use of mutual information to compare the input and encoded output in terms of accuracy for the currently most efficient encoders that use either memory based event triggering (MBET) or deadband error modulation (DEM). This allows a practitioner to select a suitable encoder for a given input specification.