Smart Implementation of Industrial Internet of Things Using Embedded Mechatronic System
Abdelhamid Zaïdi, Ismail Keshta, Zatin Gupta, Prachi Pundhir, Tripti Pandey, Praveen Kumar Rai, Mohammad Shabaz, Mukesh Soni
Abstract
In Industry 4.0, integrating IIoT and smart manufacturing is crucial for high-quality, efficient, and cost-effective production. However, the performance of IIoT systems can be hindered by unevenly distributed ESPs. To tackle this challenge, we propose an optimized embedded system for edge intelligence and smart manufacturing, leveraging digital twin technology. Our approach employs a digital twin-assisted alliance game resource optimization strategy to jointly optimize multi-dimensional resource allocation, including bandwidth, computing, and caching resources, while considering constraints like maximum delay. The optimization problem maximizes edge terminal utility and ESP utility, transformed into a convex optimization problem with linear constraints. An approximate optimal solution is obtained through an alternating iterative method. Simulation results demonstrate significant enhancements in resource utilization efficiency compared to baseline schemes like Nash equilibrium and large coalition. The proposed scheme is ideal for large-scale edge intelligence and smart manufacturing systems, with benefits increasing alongside the number of ESPs.