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Volume 14
Issue 6
10.3390/jsan14060108
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Implementation of a Cloud-Based AI-Enabled Monitoring System in Machining, Utilizing Public 5G Infrastructure †

by
Grigorios Kotsakis
1,
Christos Papaioannou
1,
Thanassis Souflas
1,
Dimitris Tsolkas
2,
Alex Kakyris
2,
Panagiotis Gounas
3 and
Panagiotis Stavropoulos
1,*
1
Laboratory for Manufacturing Systems & Automation (LMS), Department of Mechanical Engineering & Aeronautics, University of Patras, 26504 Patras, Greece
2
Fogus Innovations & Services, Michali Karaoli 51-53, 16121 Athens, Greece
3
CNC Solutions—Panagiotis Gounas Konstantinos Enezlis O.E., 19th km Athens-Lavrion, 19002 Athens, Greece
*
Author to whom correspondence should be addressed.
†
This paper is an extended version of our paper published in Kotsakis, G.; Papaioannou, C.; Souflas, T.; Tsolkas, D.; Kakyris, A.; Gounas, P.; Stavropoulos, P. Development and Implementation of an Architecture for Cloud-Based Monitoring in Machining, Focusing on High Performance Applications. Procedia CIRP 2025, 133, 579–584. https://doi.org/10.1016/j.procir.2025.02.099.
J. Sens. Actuator Netw. 2025, 14(6), 108; https://doi.org/10.3390/jsan14060108 (registering DOI)
Submission received: 30 September 2025 / Revised: 24 October 2025 / Accepted: 29 October 2025 / Published: 31 October 2025
(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)
Versions Notes

Abstract

Cloud monitoring systems combine physical sensors with cloud computing capabilities. Modern manufacturing techniques and smart factories under Industry 4.0 and Industry 5.0 call for the integration of monitoring systems as part of the broader digitization process. Digitization typically occurs by integrating external sensors onto existing legacy machines. Data obtained can be utilized in digital twins, simulations, machine learning models, and Industrial Internet Of Things (IIoT) applications. The adaptation of these new technologies usually stalls due to the reluctance of end users to make modifications to already existing equipment, the legacy equipment that is in use and does not provide the information needed, and the substantial costs of integrating new measuring systems that typically require additional IT infrastructure. Having identified the need for easily scalable affordable measurement systems, new disseminated systems that utilize cloud solutions and use 5G as an enabler for real-time communication are on the rise. This publication proposes a methodology, and tests and demonstrates a relevant manufacturing use case for integrating a non-invasive-to-IT-infrastructure, cloud-based and artificial intelligence-powered monitoring system focused on high performance applications. The proposed methodology has been evaluated in a real industrial environment.
Keywords: ΙΙοΤ; manufacturing; 5G; SaaS; CPS ΙΙοΤ; manufacturing; 5G; SaaS; CPS

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MDPI and ACS Style

Kotsakis, G.; Papaioannou, C.; Souflas, T.; Tsolkas, D.; Kakyris, A.; Gounas, P.; Stavropoulos, P. Implementation of a Cloud-Based AI-Enabled Monitoring System in Machining, Utilizing Public 5G Infrastructure. J. Sens. Actuator Netw. 2025, 14, 108. https://doi.org/10.3390/jsan14060108

AMA Style

Kotsakis G, Papaioannou C, Souflas T, Tsolkas D, Kakyris A, Gounas P, Stavropoulos P. Implementation of a Cloud-Based AI-Enabled Monitoring System in Machining, Utilizing Public 5G Infrastructure. Journal of Sensor and Actuator Networks. 2025; 14(6):108. https://doi.org/10.3390/jsan14060108

Chicago/Turabian Style

Kotsakis, Grigorios, Christos Papaioannou, Thanassis Souflas, Dimitris Tsolkas, Alex Kakyris, Panagiotis Gounas, and Panagiotis Stavropoulos. 2025. "Implementation of a Cloud-Based AI-Enabled Monitoring System in Machining, Utilizing Public 5G Infrastructure" Journal of Sensor and Actuator Networks 14, no. 6: 108. https://doi.org/10.3390/jsan14060108

APA Style

Kotsakis, G., Papaioannou, C., Souflas, T., Tsolkas, D., Kakyris, A., Gounas, P., & Stavropoulos, P. (2025). Implementation of a Cloud-Based AI-Enabled Monitoring System in Machining, Utilizing Public 5G Infrastructure. Journal of Sensor and Actuator Networks, 14(6), 108. https://doi.org/10.3390/jsan14060108

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