Edge Intelligence for Real-Time Industrial IoT Applications in Smart Manufacturing

Abstract

This article discusses edge intelligence and its role in real-time industrial Internet of Things (IoT) applications in smart manufacturing settings. The series of experiments described herein provide evidence that using an edge computing architecture result in lower latency, higher reliability, better security and faster decision making compared to using a solely cloud-based infrastructure. The experiments provided insight into how to integrate various elements together to allow production data to be processed as close to the point of origin as possible using sensors, edge nodes, machine-learning models and communications protocols in order to enable the capabilities of edge intelligence. The article also describes additional benefits of having localized intelligence for predictive maintenance, quality inspection, energy optimization and operational safety purposes. A structured means for deploying edge-based industrial IoT systems in smart factories is described followed by an exploration of performance advantages such as reduced delays, improved accuracy of response times and increased resilience of the overall system. In conclusion, the results of this research study indicate that edge-based solutions provide a practical and scalable solution to modern manufacturing, especially when continuous monitoring and rapid response are necessary to ensure a manufacturer is able to compete in today’s highly competitive industrial environment.