Industry 5.0 in Industrial and Academic Applications
Michał Ziemiński1, Monika Rybczak2

1Monika Rybczak, Department of Ship Automation, Gdynia University Maritime Gdynia, Poland.
2Michał Ziemiński, Department of Ship Automation, Gdynia University Maritime Gdynia, Poland.
Manuscript received on 17 October 2022 | Revised Manuscript received on 31 October 2022 | Manuscript Accepted on 15 November 2022 | Manuscript published on 30 November 2022 | PP: 22-25 | Volume-11 Issue-12, November 2022 | Retrieval Number: 100.1/ijitee.L932511111222 | DOI: 10.35940/ijitee.L9325.11111222
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Abstract: Technology 5.0 combines analytical thinking algorithms with leading technologies such as the Internet of Things, smart factory, cobots and artificial intelligence. With the growth of manufacturing, the digitization process is the only way to ensure further growth opportunities in the future. The article presents the most important features of technology 5.0, according to the authors. They found several examples in the literature related to artificial intelligence. Two extreme examples are then presented. An academic testbed using an artificial intelligence module built at the Maritime University of Gdynia, Faculty of Electrical Engineering. We propose a testbed configuration based on image recognition based on the S7-1500 controller and Intel RealSense camera. The first example shows how to configure the Linux environment and Phyton language needed for teaching artificial intelligence. Steps for implementing the learned AI model into a Siemens Neutral Processing Unit (NPU) module are given. This provides a glimpse of academic solutions. Recognized as the theoretical methods needed for artificial intelligence module research. The second example provides general information about the application of 5.0 technology at GPEC (Thermal Energy Company – Gdansk ). It provides a broader view of the application of 5.0 technology in industry. The results chapter compares the proposed two solutions based on the described technology, showing the potential of both solutions, which are closely related to artificial intelligence algorithms. According to the authors, they are based on image recognition based on a classification algorithm and machine learning techniques. The authors propose a prototype of the test bed needed for Internet 5.0 research in laboratory conditions while giving general applications in industrial conditions. 
Keywords: Artificial Intelligence, Decision Tree, Machine Learning, Neural Networks, Programmable Logic Controllers.
Scope of the Article: Artificial Intelligence