From Surveillance to Digital Twin: Challenges and Recent Advances of Signal Processing for Industrial Internet of Things

Abstract

With the recent advances in the Internet of Things (IoT), the significance of information technologies to modern industry is upgraded from purely providing surveillance-centric functions to building a comprehensive information framework of the industrial processes. Innovative techniques and concepts emerge under such circumstances, e.g., digital twin, which essentially involves data acquisition, human-machine-product interconnection, knowledge discovery and generation, and intelligent control, etc. Signal processing techniques are crucial to the aforementioned procedures but face unprecedented challenges when they are applied in the complex industrial environments. In this article, we survey the promising industrial applications of IoT technologies and discuss the challenges and recent advances in this area. We also share our early experience with Pavatar, a real-world industrial IoT system that enables comprehensive surveillance and remote diagnosis for ultrahigh-voltage converter station (UHVCS). Potential research challenges in building such a system are also categorized and discussed to illuminate the future directions.