THE UTILIZATION OF 6G IN INDUSTRY 4.0

Hanan M. SHUKUR


Al-Kitab University (Iraq)
https://orcid.org/0000-0002-8420-5331

Shavan ASKAR

shavan.askar@epu.edu.iq
EPU (Iraq)
https://orcid.org/0000-0002-9279-8181

Subhi R.M. ZEEBAREE


DPU (Iraq)
https://orcid.org/0000-0002-3895-2619

Abstract

 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.


Keywords:

6G, Industry 4.0, AI, IoT, Industrial Applications

Abdulazeez, D. H, & Askar, S. K. (2023). Offloading mechanisms based on reinforcement learning and deep learning algorithms in the fog computing environment. IEEE Access, 11, 12555-12586. https://doi.org/10.1109/ACCESS.2023.3241881
DOI: https://doi.org/10.1109/ACCESS.2023.3241881   Google Scholar

Abdulazeez, D. H, & Askar, S. K. (2024). A novel offloading mechanism leveraging fuzzy logic and Deep Reinforcement Learning to improve IoT application performance in a three-layer architecture within the Fog-Cloud environment. IEEE Access, 12, 39936-39952. https://doi.org/10.1109/ACCESS.2024.3376670
DOI: https://doi.org/10.1109/ACCESS.2024.3376670   Google Scholar

Achouch, M., Dimitrova, M., Ziane, K., Sattarpanah Karganroudi, S., Dhouib, R., Ibrahim, H., & Adda, M. (2022). On predictive maintenance in Industry 4.0: Overview, models, and challenges. Applied Sciences, 12(16), 8081. https://doi.org/10.3390/app12168081
DOI: https://doi.org/10.3390/app12168081   Google Scholar

Ahammed, T. B., & Patgiri, R. (2020). 6G and AI: The emergence of future forefront technology. 2020 Advanced Communication Technologies and Signal Processing (ACTS) (pp. 1-6). IEEE. https://doi.org/10.1109/ACTS49415.2020.9350396
DOI: https://doi.org/10.1109/ACTS49415.2020.9350396   Google Scholar

Akhtar, M. W., Hassan, S. A., Ghaffar, R., Jung, H., Garg, S., & Hossain, M. S. (2020). The shift to 6G communications: vision and requirements. Human-centric Computing and Information Sciences, 10, 53. https://doi.org/10.1186/s13673-020-00258-2
DOI: https://doi.org/10.1186/s13673-020-00258-2   Google Scholar

Al-Jaroodi, J., Abukhousa, E., & Mohamed, N. (2020). Health 4.0: On the way to realizing the healthcare of the future. IEEE Access, 8, 211189-211210. https://doi.org/10.1109/access.2020.3038858
DOI: https://doi.org/10.1109/ACCESS.2020.3038858   Google Scholar

Alshahrani, H., Maray, M., Aljebreen, M., Alymani, M., Ahmed Elfaki, M., Al Duhayyim, M., Balaji, P., & Gupta, D. (2023). Energy aware routing with optimal deep learning based anomaly detection in 6G-IoT networks. Sustainable Energy Technologies and Assessments, 60, 103494. https://doi.org/10.1016/j.seta.2023.103494
DOI: https://doi.org/10.1016/j.seta.2023.103494   Google Scholar

Assad, F., Konstantinov, S., Nureldin, H., Waseem, M., Rushforth, E., Ahmad, B., & Harrison, R. (2021). Maintenance and digital health control in smart manufacturing based on condition monitoring. Procedia CIRP, 97, 142-147. https://doi.org/https://doi.org/10.1016/j.procir.2020.05.216
DOI: https://doi.org/10.1016/j.procir.2020.05.216   Google Scholar

Bécue, A., Praça, I., & Gama, J. (2021). Artificial intelligence, cyber-threats and Industry 4.0: challenges and opportunities. Artificial Intelligence Review, 54(5), 3849-3886. https://doi.org/10.1007/s10462-020-09942-2
DOI: https://doi.org/10.1007/s10462-020-09942-2   Google Scholar

Dang, S., Amin, O., Shihada, B., & Alouini, M.-S. (2020). What should 6G be? Nature Electronics, 3, 20-29. https://doi.org/10.1038/s41928-019-0355-6
DOI: https://doi.org/10.1038/s41928-019-0355-6   Google Scholar

Darman, I., Mahmood, M. K., Chaudhry, S. A., Khan, S. A., & Lim, H. (2022). Designing an enhanced user authenticated key management scheme for 6G-based industrial applications. IEEE Access, 10, 92774-92787. https://doi.org/10.1109/ACCESS.2022.3198642
DOI: https://doi.org/10.1109/ACCESS.2022.3198642   Google Scholar

Deng, J., Zeng, J., Mai, S., Jin, B., Yuan, B., You, Y., Lu, S., & Yang, M. (2021). Analysis and prediction of ship energy efficiency using 6G big data internet of things and artificial intelligence technology. International Journal of System Assurance Engineering and Management, 12, 824–834. https://doi.org/10.1007/s13198-021-01116-9
DOI: https://doi.org/10.1007/s13198-021-01116-9   Google Scholar

Dohler, M., Mahmoodi, T., Lema, M. A., Condoluci, M., Sardis, F., Antonakoglou, K., & Aghvami, H. (2017). Internet of skills, where robotics meets AI, 5G and the Tactile Internet. 2017 European Conference on Networks and Communications (EuCNC) (pp. 1-5). IEEE. https://doi.org/10.1109/EuCNC.2017.7980645
DOI: https://doi.org/10.1109/EuCNC.2017.7980645   Google Scholar

Elaziz, M. A., Dahou, A., Mabrouk, A., Ibrahim, R. A., & Aseeri, A. O. (2023). Medical image classifications for 6G IoT-Enabled smart health systems. Diagnostics, 13(5), 834. https://doi.org/10.3390/diagnostics13050834
DOI: https://doi.org/10.3390/diagnostics13050834   Google Scholar

Faouzi, D., Pallathadka, H., Abdullaev, S., Asaad, R. R., Aska, S., & Haroon, N. H. (2023). Probing the impact of process variables in laser-welded aluminum alloys: A Machine Learning study. Materials Today Communications, 38, 107660. https://doi.org/10.1016/j.mtcomm.2023.107660
DOI: https://doi.org/10.1016/j.mtcomm.2023.107660   Google Scholar

Ghildiyal, Y., Singh, R., Alkhayyat, A., Gehlot, A., Malik, P., Sharma, R., Akram, S. V., & Alkwai, L. M. (2023). An imperative role of 6G communication with perspective of industry 4.0: Challenges and research directions. Sustainable Energy Technologies and Assessments, 56, 103047. https://doi.org/10.1016/j.seta.2023.103047
DOI: https://doi.org/10.1016/j.seta.2023.103047   Google Scholar

Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869. https://doi.org/10.1016/j.jclepro.2019.119869
DOI: https://doi.org/10.1016/j.jclepro.2019.119869   Google Scholar

Gui, G., Liu, M., Tang, F., Kato, N., & Adachi, F. (2020). 6G: Opening new horizons for integration of comfort, security, and intelligence. IEEE Wireless Communications, 27(5), 126-132. https://doi.org/10.1109/MWC.001.1900516
DOI: https://doi.org/10.1109/MWC.001.1900516   Google Scholar

Feng, H., Cui, Z., Han, C., Ning, J., & Yang, T. (2021). Bidirectional green promotion of 6G and AI: Architecture, solutions, and platform, IEEE Network, 35(6), 57-63. https://doi.org/10.1109/MNET.101.2100285
DOI: https://doi.org/10.1109/MNET.101.2100285   Google Scholar

Han, B., Habibi, M. A., Richerzhagen, B., Schindhelm, K., Zeiger, F., Lamberti, F., Pratticò, F. G., Upadhya, K., Korovesis, C., Belikaidis, I.-P., Demestichas, P., Yuan, S., & Schotten, H. D. (2023). Digital twins for Industry 4.0 in the 6G era. IEEE Open Journal of Vehicular Technology, 4, 820-835. https://doi.org/10.1109/OJVT.2023.3325382
DOI: https://doi.org/10.1109/OJVT.2023.3325382   Google Scholar

Han, S., Xie, T., & Li, C.-L. (2021). Greener physical layer technologies for 6G mobile communications, IEEE Communications Magazine, 59(4), 68-74. https://doi.org/10.1109/MCOM.001.2000484
DOI: https://doi.org/10.1109/MCOM.001.2000484   Google Scholar

Harahap, T. H., Mansouri, S., Abduallah, O. S., Uinarni, H., Askar, S., Jabbar, T. L., Alawadi, A. H., & Hassan, A. Y. (2024). An artificial intelligence approach to predict infants’ health status at birth. International Journal of Medical Informatics, 183, 105338. https://doi.org/10.1016/j.ijmedinf.2024.105338
DOI: https://doi.org/10.1016/j.ijmedinf.2024.105338   Google Scholar

Hijji, M., Iqbal, R., Pandey, A. K., Doctor, F., Karyotis, C., Rajeh, W., Alshehri, A., & Aradah, F. (2023). 6G connected vehicle framework to support intelligent road maintenance using Deep Learning data fusion. IEEE Transactions on Intelligent Transportation Systems, 24(7), 7726-7735. https://doi.org/10.1109/TITS.2023.3235151
DOI: https://doi.org/10.1109/TITS.2023.3235151   Google Scholar

Hussein, D. H., & Askar, S. (2023). Federated learning enabled SDN for routing emergency safety messages (ESMs) in IoV under 5G environment. IEEE Access, 11, 141723-141739. https://doi.org/10.1109/ACCESS.2023.3343613
DOI: https://doi.org/10.1109/ACCESS.2023.3343613   Google Scholar

Ibrahim, M. A., & Askar, S. (2023). An intelligent scheduling strategy in fog computing system based on multi-objective deep reinforcement learning algorithm. IEEE Access, 11, 133607-133622. https://doi.org/10.1109/ACCESS.2023.3337034
DOI: https://doi.org/10.1109/ACCESS.2023.3337034   Google Scholar

Jiang, W., Han, B., Habibi, M. A., & Schotten, H. (2021). The road towards 6G: A comprehensive survey. IEEE Open Journal of the Communications Society, 2, 334-366. https://doi.org/10.1109/OJCOMS.2021.3057679
DOI: https://doi.org/10.1109/OJCOMS.2021.3057679   Google Scholar

Kuruvatti, N. P., Habibi, M. A., Partani, S., Han, B., Fellan, A., & Schotten, H. D. (2022). Empowering 6G communication systems with digital twin technology: A comprehensive survey. IEEE Access, 10, 112158-112186. https://doi.org/10.1109/ACCESS.2022.3215493
DOI: https://doi.org/10.1109/ACCESS.2022.3215493   Google Scholar

Liang, J., Li, L., & Zhao, C. (2021). A transfer learning approach for compressed sensing in 6G-IoT. IEEE Internet of Things Journal, 8(20), 15276-15283. https://doi.org/10.1109/JIOT.2021.3053088
DOI: https://doi.org/10.1109/JIOT.2021.3053088   Google Scholar

Liu, G., Huang, Y., Li, N., Dong, J., Jin, J., Wang, Q., & Li, N. (2020). Vision, requirements and network architecture of 6G mobile network beyond 2030. China Communications,, 17(9), 92-104,. https://doi.org/10.23919/JCC.2020.09.008
DOI: https://doi.org/10.23919/JCC.2020.09.008   Google Scholar

Liu, S., & Zhang, J. (2021). Local alignment deep network for infrared-visible cross-modal person reidentification in 6G-enabled Internet of Things. IEEE Internet of Things Journal, 8(20), 15170-15179. https://doi.org/10.1109/JIOT.2020.3038794
DOI: https://doi.org/10.1109/JIOT.2020.3038794   Google Scholar

Uusitalo, M. A., Rugeland, P., Boldi, M. R., Strinati, E. C., Demestichas, P., Ericson, M., Fettweis, G. P., Filippou, M. C., Gati, A., Hamon, M.-H., Hoffmann, M., Latva-aho, M., Pärssinen, A., Richerzhagen, B., Schotten, H., Svensson, T., Wikström, G., Wymeersch, H., Ziegler, V., & Zou, Y. (2021). 6G vision, value, use cases and technologies from European 6G agship project Hexa-X. IEEE Access, 9, 160004-160020. https:/doi.org/10.1109/ACCESS.2021.3130030
DOI: https://doi.org/10.1109/ACCESS.2021.3130030   Google Scholar

Mahmood, N. H., Berardinelli, G., Khatib, E. J., Hashemi, R., Lima, C. D., & Latva-aho, M. (2023). A functional architecture for 6G special-purpose industrial IoT networks. IEEE Transactions on Industrial Informatics, 19(3), 2530-2540. https://doi.org/10.1109/TII.2022.3182988
DOI: https://doi.org/10.1109/TII.2022.3182988   Google Scholar

Mao, B., Tang, F., Kawamoto, Y., & Kato, N. (2021). Optimizing computation offloading in satellite-UAV-served 6G IoT: A Deep Learning approach. IEEE Network, 35(4), 102-108. https://doi.org/10.1109/MNET.011.2100097
DOI: https://doi.org/10.1109/MNET.011.2100097   Google Scholar

Mezair, T., Djenouri, Y., Belhadi, A., Srivastava, G., & Lin, J. C.-W. (2022). A sustainable deep learning framework for fault detection in 6G Industry 4.0 heterogeneous data environments. Computer Communications, 187, 164-171. https://doi.org/10.1016/j.comcom.2022.02.010
DOI: https://doi.org/10.1016/j.comcom.2022.02.010   Google Scholar

Nashwan, S., & Nashwan, I. I. H. (2021). Reducing the overhead messages cost of the SAK-AKA authentication scheme for 4G/5G mobile networks. IEEE Access, 9, 97539-97545. https://doi.org/10.1109/ACCESS.2021.3094045
DOI: https://doi.org/10.1109/ACCESS.2021.3094045   Google Scholar

Nayak, S., & Patgiri, R. (2020a). 6G communication: Envisioning the key issues and challenges. EAI Endorsed Transactions on Internet of Things, 6(24), e1. https://doi.org/10.4108/eai.11-11-2020.166959
DOI: https://doi.org/10.4108/eai.11-11-2020.166959   Google Scholar

Nayak, S., & Patgiri, R. (2020b). A vision on intelligent medical service for emergency on 5G and 6G communication era. EAI Endorsed Transactions on Internet of Things, 6(22), e2. https://doi.org/10.4108/eai.17-8-2020.166293
DOI: https://doi.org/10.4108/eai.17-8-2020.166293   Google Scholar

Porambage, P., Gür, G., Osorio, D. P. M., Liyanage, M., Gurtov, A., & Ylianttila, M. (2021). The roadmap to 6G security and privacy. IEEE Open Journal of the Communications Society, 2, 1094-1122. https://doi.org/10.1109/OJCOMS.2021.3078081
DOI: https://doi.org/10.1109/OJCOMS.2021.3078081   Google Scholar

Padhi, P. K., & Charrua-Santos, F. (2021). 6G enabled industrial internet of everything: Towards a theoretical framework. Applied System Innovation, 4(1), 11. https://doi.org/10.3390/asi4010011
DOI: https://doi.org/10.3390/asi4010011   Google Scholar

Pallathadka, H., Naser, S. J., Askar, S., Al. Husseini, E. Q., Abdullaeva, B. S., & Haroon, N. H. (2023). Scheduling of multiple energy consumption in the smart buildings with peak demand management. International Journal of Integrated Engineering, 15(4), 311-321.
DOI: https://doi.org/10.30880/ijie.2023.15.04.027   Google Scholar

Pech, M., Vrchota, J., & Bednář, J. (2021). Predictive maintenance and intelligent sensors in smart factory: review. Sensors, 21(4), 1470. https://doi.org/10.3390/s21041470
DOI: https://doi.org/10.3390/s21041470   Google Scholar

Qi, Q., Chen, X., Zhong, C., & Zhang, Z. (2020). Integration of energy, computation and communication in 6G cellular Internet of Things. IEEE Communications Letters, 24(6), 1333-1337. https://doi.org/10.1109/LCOMM.2020.2982151
DOI: https://doi.org/10.1109/LCOMM.2020.2982151   Google Scholar

Rao, S. K. (2021). Data-driven business model innovation for 6G. Journal of ICT Standardization, 9(03), 405-426. https://doi.org/10.13052/jicts2245-800X.935
DOI: https://doi.org/10.13052/jicts2245-800X.935   Google Scholar

Sarker, I. H. (2021). Machine Learning: Algorithms, real-world applications and research directions. SN Computer Science, 2, 160. https://doi.org/10.1007/s42979-021-00592-x
DOI: https://doi.org/10.1007/s42979-021-00592-x   Google Scholar

Shahraki, A., Abbasi, M., Piran, M. J., & Taherkordi, A. (2021). A comprehensive survey on 6G networks: Applications, core services, enabling technologies, and future challenges. arXiv, abs/2101.12475. https://doi.org/10.48550/arXiv.2101.12475
  Google Scholar

Sharma, I., Gupta, K. S., Mishra, A., & Askar, S. (2023). Synchronous federated learning based multi unmanned aerial vehicles for secure applications. Scalable Computing Practice and Experience, 24(3), 191-201. https://doi.org/10.12694/scpe.v24i3.2136
DOI: https://doi.org/10.12694/scpe.v24i3.2136   Google Scholar

Silvestri, L., Forcina, A., Introna, V., Santolamazza, A., & Cesarotti, V. (2020). Maintenance transformation through Industry 4.0 technologies: A systematic literature review. Computers in Industry, 123, 103335. https://doi.org/https://doi.org/10.1016/j.compind.2020.103335
DOI: https://doi.org/10.1016/j.compind.2020.103335   Google Scholar

Sliwa, B., Adam, R., & Wietfeld, C. (2021). Client-based intelligence for resource efficient vehicular big data transfer in future 6G networks. IEEE Transactions on Vehicular Technology, 70(6), 5332-5346. https://doi.org/10.1109/TVT.2021.3060459
DOI: https://doi.org/10.1109/TVT.2021.3060459   Google Scholar

Tariq, F., Khandaker, M. R. A., Wong, K.-K., Imran, M. A., Bennis, M., & Debbah, M. (2020). A speculative study on 6G, IEEE Wireless Communications Magazine,, 27(4), 118-125. https://doi.org/ 10.1109/MWC.001.1900488
DOI: https://doi.org/10.1109/MWC.001.1900488   Google Scholar

Wang, S., Qureshi, M., Miralles-Pechuan, L., Huynh-The, T., Gadekallu, T., & Liyanage, M. (2021). Applications of explainable AI for 6G: Technical aspects, use cases, and research challenges. ArXiv abs/2112.04698. https://doi.org/10.48550/arXiv.2112.04698
  Google Scholar

Wang, W., Liu, F., Zhi, X., Zhang, T., & Huang, C. (2021). An integrated Deep Learning algorithm for detecting lung nodules with low-dose CT and its application in 6G-enabled internet of medical things. IEEE Internet of Things Journal, 8(7), 5274-5284. https://doi.org/10.1109/JIOT.2020.3023436
DOI: https://doi.org/10.1109/JIOT.2020.3023436   Google Scholar

Wang, Y., Tian, Y., Hei, X., Zhu, L., & Ji, W. (2021). A novel IoV block-streaming service awareness and trusted verification scheme in 6G. IEEE Transactions on Vehicular Technology, 70(6), 5197-5210. https://doi.org/10.1109/TVT.2021.3063783
DOI: https://doi.org/10.1109/TVT.2021.3063783   Google Scholar

Zhang, S., & Zhu, D. (2020). Towards artificial intelligence enabled 6G: State of the art, challenges, and opportunities. Computer Networks, 183, 107556. https://doi.org/https://doi.org/10.1016/j.comnet.2020.107556
DOI: https://doi.org/10.1016/j.comnet.2020.107556   Google Scholar

Download


Published
2024-06-30

Cited by

M. SHUKUR, H., ASKAR, S., & R.M. ZEEBAREE, S. (2024). THE UTILIZATION OF 6G IN INDUSTRY 4.0. Applied Computer Science, 20(2), 75–89. https://doi.org/10.35784/acs-2024-17

Authors

Hanan M. SHUKUR 

Al-Kitab University Iraq
https://orcid.org/0000-0002-8420-5331

Authors

Subhi R.M. ZEEBAREE 

DPU Iraq
https://orcid.org/0000-0002-3895-2619

Statistics

Abstract views: 282
PDF downloads: 117


License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.


Similar Articles

1 2 3 4 5 6 7 > >> 

You may also start an advanced similarity search for this article.