An industrial IoT edge node for buffer level detection in a cardboard production line
G. Avramidis, Dimitris Karampatzakis · IOP Conference Series Materials Science and Engineering · 2021
Abstract Computer Science and Internet have evolved rapidly the last decades and equally impressive is the evolution of the Industrial Internet of Things technology into factories’ shop floors. Among other technologies: modern CPU Architectures, Edge Computing, Deep Learning, Computer Vision, and Low Power Wide Area Networks, are playing a key role in this new competitive environment. In this paper, we present an Industrial IoT Edge Node for level detection on an overhead bridge conveyor (buffer) which is part of a 5-ply corrugated cardboard production line. We focused on the Edge Node and the development of the system was accomplished by using state of the art technologies from disciplines of computer vision and deep learning. We present two implementations using contour detection and CNN techniques. Finally, we implemented a LoRaWAN solution in the IIoT node to send alert messages to the control room. Experimental results are presented for the proposed system implementations.