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2 2024

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The utilization of 6G in Industry 4.0

Shukur Hanan M., Askar Shavan, Zeebaree Subhi R.M.

Applied Computer Science

2024

Vol. 20, no. 2

75--89

The sixth-generation (6G) communication technology has potential in various applications, for instance, industrial automation, intelligent transportation, healthcare systems, and energy consumption prediction. On the other hand, the concerns of privacy measures and security measures in 6G-enabled networks are considered critical issues and challenges. The integration of 6G with advanced technologies for example computing, Artificial Intelligence (AI), and Internet of Things (IoT) is a common theme in this paper. Additionally, the paper discusses the challenges and advancements required for 6G technology to be utilized with other technologies, involving edge technology, big data analytics, and deep learning. In this review paper, the authors overview the integration of 6G with cutting-edge technologies like IoT, IoMT, AI, and edge computing that address human requirements and issues. In addition, to make values for new technologies like Big data, federated learning machine learning, deep learning, and multiple aspects are merged collectively to offer a network for the machine and human growing era. These integrations can be utilized for monitoring energy consumption in real-time, intelligent transportation solutions, improved security in industrial applications, signal reconstruction, and industrial automation. Additionally, the authors illustrate the critical considerations and challenges that face the integration of 6G for instance, performance requirements, security, and privacy concerns. Overall, this paper suggests that 6G communication technology can revolutionize different sides of our society, and enhance efficiency and accuracy in various future industrial automation and sectors.

Exploring the impact of artificial intelligence on humanrobot cooperation in the context of Industry 4.0

Asaad Hawkar, Askar Shavan, Kakami Ahmed, Faiq Nayla

Applied Computer Science

2024

Vol. 20, no. 2

138--156

The function of Artificial Intelligence (AI) in Human-Robot Cooperation (HRC) in Industry 4.0 is unequivocally important and cannot be undervalued. It uses Machine Learning (ML) and Deep Learning (DL) to enhance collaboration between humans and robots in smart manufacturing. These algorithms effectively manage and analyze data from sensors, machinery, and other associated entities. As an outcome, they can extract significant insights that can be beneficial in optimizing the manufacturing process overall. Because dumb manufacturing systems hinder coordination, collaboration, and communication among various manufacturing process components. Consequently, efficiency, quality, and productivity all suffer as a whole. Additionally, Artificial Intelligence (AI) makes it possible to implement sophisticated learning processes that enhance human-robot collaboration and effectiveness when it comes to assembly tasks in the manufacturing domain by enabling learning at a level that is comparable to human-human interactions. When Artificial Intelligence (AI) is widely applied in Human-Robot Cooperation (HRC), a new and dynamic environment for human-robot collaboration is created and responsibilities are divided and distributed throughout social and physical spaces. In conclusion, Artificial Intelligence (AI) plays a crucial and indispensable role in facilitating effective and efficient Human-Robot Cooperation (HRC) within the framework of Industry 4.0. The implementation of Artificial Intelligence (AI)-based algorithms, encompassing deep learning, machine learning, and reinforcement learning, is highly consequential as it enhances human-robot collaboration, streamlines production procedures, and boosts overall productivity, quality, and efficiency in the manufacturing industry.