A Modified Differential Evolution with Heuristics Algorithm for Non-convex Optimization on Sensor Network Localization

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Toward intelligent cyber-physical systems: Digital twin meets artificial intelligence

Industry 4.0 aims to support smarter and autonomous processes while improving agility, cost efficiency, and user experience. To fulfill its promises, properly processing the data of the industrial processes and infrastructures is required. Artificial intelligence (AI) appears as a strong candidate to handle all generated data, and to help in the automation and smartification process. This article overviews the digital twin as a true embodiment of a cyber-physical system (CPS) in Industry 4.0, showing the mission of AI in this concept. It presents the key enabling technologies of the digital twin such as edge, fog, and 5G, where the physical processes are integrated with the computing and network domains. The role of AI in each technology domain is identified by analyzing a set of AI agents at the application and infrastructure levels. Finally, movement prediction is selected and experimentally validated using real data generated by a digital twin for robotic arms with results showcasing its potential.This work has been (partially) funded by the H2020 EU/TW joint action 5G-DIVE (Grant #859881) and the H2020 5Growth project (Grant #856709). It has also been funded by the Spanish State Research Agency (TRUE5G project, PID2019-108713RB-C52/AEI/10.13039/501100011033)