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A Survey on AI Integration into Industry 5.0

Year 2025, Early View, 1 - 1
https://doi.org/10.35378/gujs.1320760

Abstract

Industry 5.0 (IR 5.0) is a modern production model focused on human-machine collaboration. The goal is to maintain a balance between machine and human interaction, with an emphasis on creative production and customization. Artificial intelligence (AI) will play a key role in IR 5.0 as it enables intelligent manufacturing and transforms many aspects of society. Technologies such as AI, Internet of Things (IoT), Blockchain, Virtual Reality (VR)/Augmented Reality (AR), Big Data Analytics and Cyber-Physical Systems (CPS) are essential to achieve the goals of an intelligent society. This article explores the integration of AI in IR 5.0. However, there are some challenges to overcome such as data security, ethical concerns, employee training, black box AI, etc. Despite its challenges, AI integration to IR 5.0 promises to drive automation, efficiency, and customization in manufacturing. To ensure inclusive and sustainable development, the social implications and impacts of IR 5.0 must be carefully considered.

References

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  • [2] Kurt. R., “Industry 4.0 in terms of industrial relations and its impacts on labour life”, Procedia Computer Science, 158, 590-601, (2019).
  • [3] Patrício, L., Sangiorgi, D., Mahr, D., Čaić, M., Kalantari, S., Sundar, S., “Leveraging service design for healthcare transformation: Toward people-centered, integrated, and technology-enabled healthcare systems”, Journal of Service Management, 31(5): 889-909, (2020).
  • [4] Maddikunta, P. K. R., Pham, Q. V., Prabadevi, B., Deepa, N., Dev, K., Gadekallu, T. R., Liyanage, M., “Industry 5.0: A survey on enabling technologies and potential applications”, Journal of Industrial Information Integration, 26: 100257, (2022).
  • [5] Pilevari, N., “Industry Revolutions Development from Industry 1.0 to Industry 5.0 in Manufacturing”, Journal of Industrial Strategic Management, 5(2): 44-63, (2020).
  • [6] Gourisaria, M. K., Agrawal, R., Harshvardhan, G. M., Pandey, M., Rautaray, S. S., “Application of Machine Learning in Industry 4.0”, In Machine Learning: Theoretical Foundations and Practical Applications, Springer, Singapore, 57-87, (2021).
  • [7] Ozdemir, V., Hekim, N., “Birth of industry 5.0: Making sense of big data with artificial intelligence, the internet of things and next-generation technology policy”, Omics: A Journal of Integrative Biology, 22(1): 65-76, (2018).
  • [8] Paschek, D., Mocan, A., Draghici, A., “Industry 5.0-The expected impact of next Industrial Revolution. In Thriving on Future Education, Industry, Business, and Society”, Proceedings of the MakeLearn and TIIM International Conference, Piran, Slovenia, 15-17, (2019).
  • [9] Aslam, F., Aimin, W., Li, M., Ur Rehman, K., “Innovation in the era of IoT and industry 5.0: absolute innovation management (AIM) framework”, Information, 11(2): 124, (2020).
  • [10] Campero-Jurado, I., Márquez-Sánchez, S., Quintanar-Gómez, J., Rodríguez, S., & Corchado, J. M., “Smart Helmet 5.0 for industrial internet of things using artificial intelligence”, Sensors, 20(21): 6241, (2020).
  • [11] Soori, M., Arezoo, B., Dastres, R., “Artificial intelligence, machine learning and deep learning in advanced robotics, a review”, Cognitive Robotics, 3: 54-70, (2023).
  • [12] Javaid, M., Haleem, A., Suman, R., “Digital twin applications toward industry 4.0: A review”, Cognitive Robotics, 3: 71-92, (2023).
  • [13] Raja Santhi, A., Muthuswamy, P., “Industry 5.0 or industry 4.0 S? Introduction to industry 4.0 and a peek into the prospective industry 5.0 technologies”, International Journal on Interactive Design and Manufacturing (IJIDeM), 17(2): 947-979, (2023).
  • [14] Khalil, A. J., Barhoom, A. M., Abu-Nasser, B. S., Musleh, M. M., Abu-Naser, S. S., “Energy Efficiency Prediction using Artificial Neural Network”, Energy, 3(9): 1-7, (2019).
  • [15] Gupta, I., Nagpal, G., “Artificial intelligence and expert systems”, Mercury Learning and Information, (2020).
  • [16] Javaid, M., Haleem, A., Singh, R. P., & Suman, R., “Substantial capabilities of robotics in enhancing industry 4.0 implementation”, Cognitive Robotics, 1: 58-75, (2021).
  • [17] Peckol, J. K., “Introduction to fuzzy logic”, John Wiley & Sons, (2021).
  • [18] Lu, X., “Natural Language Processing and Intelligent Computer‐Assisted Language Learning (ICALL)”, The TESOL Encyclopedia of English Language Teaching, 1-6, (2018).
  • [19] Lee, J., Singh, J., & Azamfar, M., “Industrial artificial intelligence”, arXiv preprint, arXiv:1908.02150, (2019).
  • [20] Merayo, D., Rodriguez-Prieto, A., Camacho, A. M., “Comparative analysis of artificial intelligence techniques for material selection applied to manufacturing in Industry 4.0”, Procedia Manufacturing, 41: 42-49, (2019).
  • [21] LeCun, Y., Bengio, Y., Hinton, G., “Deep learning”, Nature, 521(7553): 436-444, (2015).
  • [22] Unger, N., Zheng, Y., Yue, X., Harper, K. L., “Mitigation of ozone damage to the world's land ecosystems by source sector”, Nature Climate Change, 10(2): 134-137, (2020).
  • [23] Ahmed, F., Mähönen, P., “Quantum Computing for Artificial Intelligence Based Mobile Network Optimization”, arXiv preprint, arXiv:2106.13917, (2021).
  • [24] Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Herrera, F., “Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI”, Information Fusion, 58: 82-115, (2020).
  • [25] Siau, K., Wang, W., “Artificial intelligence (AI) ethics: ethics of AI and ethical AI”, Journal of Database Management (JDM), 31(2): 74-87, (2020).
  • [26] Bleicher, J., Stanley, H., “Digitization as a catalyst for business model innovation a three-step approach to facilitating economic success”, Journal of Business Management, 12, (2017).
  • [27] Wong, Z. S., Zhou, J., Zhang, Q., “Artificial intelligence for infectious disease big data analytics”, Infection, Disease & Health, 24(1): 44-48, (2019).
  • [28] Hoffman, R. R., Mueller, S. T., Klein, G., Litman, J., “Metrics for explainable AI: Challenges and prospects”, arXiv preprint, arXiv:1812.04608, (2018).
  • [29] ElFar, O. A., Chang, C. K., Leong, H. Y., Peter, A. P., Chew, K. W., Show, P. L., “Prospects of Industry 5.0 in algae: Customization of production and new advance technology for clean bioenergy generation”, Energy Conversion and Management: X, 10: 100048, (2021).
  • [30] Walch, M., Karagiannis, D., “How to connect design thinking and cyber-physical systems: the s* IoT conceptual modelling approach”, In Proceedings of the 52nd Hawaii International Conference on System Sciences, (2019).
  • [31] Paschek, D., Mocan, A., Draghici, A., “Industry 5.0-The expected impact of next Industrial Revolution. In Thriving on Future Education, Industry, Business, and Society”, Proceedings of the MakeLearn and TIIM International Conference, Piran, Slovenia, 15-17, (2019).
  • [32] Moufaddal, M., Benghabrit, A., Bouhaddou, I., “Industry 4.0: A roadmap to digital Supply Chains”, In 2019 1st International Conference on Smart Systems and Data Science (ICSSD), 1-9, IEEE, (2019).
  • [33] Johnson, C. W., “The increasing risks of risk assessment: On the rise of artificial intelligence and non-determinism in safety-critical systems”, In the 26th Safety-Critical Systems Symposium, 15, Safety-Critical Systems Club York, UK, (2018).
  • [34] Nahavandi, S., “Robot-based motion simulators using washout filtering: Dynamic, immersive land, air, and sea vehicle training, vehicle virtual prototyping, and testing”, IEEE Systems, Man, and Cybernetics Magazine, 2(3): 6-10, (2016).
  • [35] Melnyk, L. H., Kubatko, O. V., Dehtyarova, I. B., Dehtiarova, I. B., Matsenko, O. M., Rozhko, O. D., “The effect of industrial revolutions on the transformation of social and economic systems”, Problems and Perspectives in Management, 17(4): 381-391, (2019).
  • [36] Welfare, K. S., Hallowell, M. R., Shah, J. A., Riek, L. D., “Consider the human work experience when integrating robotics in the workplace”, In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction, IEEE, 75-84, (2019).
  • [37] Saiz-Rubio, V., Rovira-Más, F., “From smart farming towards agriculture 5.0: A review on crop data management”, Agronomy, 10(2): 207, (2020).
  • [38] Sambasivam, G., Opiyo, G. D., “A predictive machine learning application in agriculture: Cassava disease detection and classification with imbalanced dataset using convolutional neural networks”, Egyptian Informatics Journal, 22(1): 27-34, (2021).
  • [39] Slayer, K. M., “Artificial Intelligence and National Security”, Congressional Research SVC Washington United States, (2020).
  • [40] Krause, P. J., Bokinala, V., “A Tutorial on Data Mining for Bayesian Networks, with a specific focus on IoT for Agriculture”, Internet of Things, 100738, (2023).
  • [41] Yıldırım, S., Jothimani, D., Kavaklioğlu, C., Başar, A., “Deep learning approaches for sentiment analysis on financial microblog dataset”, In 2019 IEEE International Conference on Big Data (Big Data), 5581-5584, IEEE, (2019).
  • [42] Rosa, M., Beloborodko, A., “Assessment and system analysis of industrial waste management”, Journal of Cleaner Production, 1, e10, (2014).
  • [43] Parr, M. K., Schmidt, A. H., “Life cycle management of analytical methods”, Journal of Pharmaceutical and Biomedical Analysis, 147, 506-517, (2018).
  • [44] Law, K., Stuart, A., Zygalakis, K., “Data assimilation”, Cham, Switzerland: Springer, 214, 52, (2015).
  • [45] Sherer, J. A., Le, J., Taal, A., “Big Data Discovery, Privacy, and the Application of Differential Privacy Mechanisms”, The Computer & Internet Lawyer, 32(7): 10-17, (2015).
  • [46] Tikkinen-Piri, C., Rohunen, A., Markkula, J., “EU General Data Protection Regulation: Changes and implications for personal data collecting companies”, Computer Law & Security Review, 34(1): 134-153, (2018).
  • [47] Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., Janowski, T., “Data governance: Organizing data for trustworthy Artificial Intelligence”, Government Information Quarterly, 37(3): 101493, (2020).
  • [48] Moret-Bonillo, V., “Can artificial intelligence benefit from quantum computing”, Progress in Artificial Intelligence, 3(2): 89-105, (2015).
  • [49] Akhtar, M. W., Hassan, S. A., Ghaffar, R., Jung, H., Garg, S., Hossain, M. S., “The shift to 6G communications: vision and requirements”, Human-centric Computing and Information Sciences, 10(1): 1-27, (2020).
  • [50] Khiadani, N., “Vision, Requirements and Challenges of Sixth Generation (6G) Networks”, In 2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), IEEE, 1-4, (2020).
  • [51] Kim, J., “Advertising in the Metaverse: Research agenda”, Journal of Interactive Advertising, 21(3): 141-144, (2021).
  • [52] Makori, E. O., “Blockchain Applications and Trends That Promote Information Management”, In Emerging Trends and Impacts of the Internet of Things in Libraries, 34-51, IGI Global, (2020).
  • [53] Seletsky, S., “The Good, the Bad, and the Inevitable About Industrial Revolution. IoT Practitioner”, https://iotpractitioner.com/the-good-the-bad-and-the-inevitable-about-industrial-revolution/. Access date: 25.02.2023
  • [54] Wang, W., Siau, K., “Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: A review and research agenda”, Journal of Database Management (JDM), 30(1): 61-79, (2019).
Year 2025, Early View, 1 - 1
https://doi.org/10.35378/gujs.1320760

Abstract

References

  • [1] Zhou, K., Liu, T., & Zhou, L., “Industry 4.0: Towards future industrial opportunities and challenges”, In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2147-2152, IEEE, (2015).
  • [2] Kurt. R., “Industry 4.0 in terms of industrial relations and its impacts on labour life”, Procedia Computer Science, 158, 590-601, (2019).
  • [3] Patrício, L., Sangiorgi, D., Mahr, D., Čaić, M., Kalantari, S., Sundar, S., “Leveraging service design for healthcare transformation: Toward people-centered, integrated, and technology-enabled healthcare systems”, Journal of Service Management, 31(5): 889-909, (2020).
  • [4] Maddikunta, P. K. R., Pham, Q. V., Prabadevi, B., Deepa, N., Dev, K., Gadekallu, T. R., Liyanage, M., “Industry 5.0: A survey on enabling technologies and potential applications”, Journal of Industrial Information Integration, 26: 100257, (2022).
  • [5] Pilevari, N., “Industry Revolutions Development from Industry 1.0 to Industry 5.0 in Manufacturing”, Journal of Industrial Strategic Management, 5(2): 44-63, (2020).
  • [6] Gourisaria, M. K., Agrawal, R., Harshvardhan, G. M., Pandey, M., Rautaray, S. S., “Application of Machine Learning in Industry 4.0”, In Machine Learning: Theoretical Foundations and Practical Applications, Springer, Singapore, 57-87, (2021).
  • [7] Ozdemir, V., Hekim, N., “Birth of industry 5.0: Making sense of big data with artificial intelligence, the internet of things and next-generation technology policy”, Omics: A Journal of Integrative Biology, 22(1): 65-76, (2018).
  • [8] Paschek, D., Mocan, A., Draghici, A., “Industry 5.0-The expected impact of next Industrial Revolution. In Thriving on Future Education, Industry, Business, and Society”, Proceedings of the MakeLearn and TIIM International Conference, Piran, Slovenia, 15-17, (2019).
  • [9] Aslam, F., Aimin, W., Li, M., Ur Rehman, K., “Innovation in the era of IoT and industry 5.0: absolute innovation management (AIM) framework”, Information, 11(2): 124, (2020).
  • [10] Campero-Jurado, I., Márquez-Sánchez, S., Quintanar-Gómez, J., Rodríguez, S., & Corchado, J. M., “Smart Helmet 5.0 for industrial internet of things using artificial intelligence”, Sensors, 20(21): 6241, (2020).
  • [11] Soori, M., Arezoo, B., Dastres, R., “Artificial intelligence, machine learning and deep learning in advanced robotics, a review”, Cognitive Robotics, 3: 54-70, (2023).
  • [12] Javaid, M., Haleem, A., Suman, R., “Digital twin applications toward industry 4.0: A review”, Cognitive Robotics, 3: 71-92, (2023).
  • [13] Raja Santhi, A., Muthuswamy, P., “Industry 5.0 or industry 4.0 S? Introduction to industry 4.0 and a peek into the prospective industry 5.0 technologies”, International Journal on Interactive Design and Manufacturing (IJIDeM), 17(2): 947-979, (2023).
  • [14] Khalil, A. J., Barhoom, A. M., Abu-Nasser, B. S., Musleh, M. M., Abu-Naser, S. S., “Energy Efficiency Prediction using Artificial Neural Network”, Energy, 3(9): 1-7, (2019).
  • [15] Gupta, I., Nagpal, G., “Artificial intelligence and expert systems”, Mercury Learning and Information, (2020).
  • [16] Javaid, M., Haleem, A., Singh, R. P., & Suman, R., “Substantial capabilities of robotics in enhancing industry 4.0 implementation”, Cognitive Robotics, 1: 58-75, (2021).
  • [17] Peckol, J. K., “Introduction to fuzzy logic”, John Wiley & Sons, (2021).
  • [18] Lu, X., “Natural Language Processing and Intelligent Computer‐Assisted Language Learning (ICALL)”, The TESOL Encyclopedia of English Language Teaching, 1-6, (2018).
  • [19] Lee, J., Singh, J., & Azamfar, M., “Industrial artificial intelligence”, arXiv preprint, arXiv:1908.02150, (2019).
  • [20] Merayo, D., Rodriguez-Prieto, A., Camacho, A. M., “Comparative analysis of artificial intelligence techniques for material selection applied to manufacturing in Industry 4.0”, Procedia Manufacturing, 41: 42-49, (2019).
  • [21] LeCun, Y., Bengio, Y., Hinton, G., “Deep learning”, Nature, 521(7553): 436-444, (2015).
  • [22] Unger, N., Zheng, Y., Yue, X., Harper, K. L., “Mitigation of ozone damage to the world's land ecosystems by source sector”, Nature Climate Change, 10(2): 134-137, (2020).
  • [23] Ahmed, F., Mähönen, P., “Quantum Computing for Artificial Intelligence Based Mobile Network Optimization”, arXiv preprint, arXiv:2106.13917, (2021).
  • [24] Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Herrera, F., “Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI”, Information Fusion, 58: 82-115, (2020).
  • [25] Siau, K., Wang, W., “Artificial intelligence (AI) ethics: ethics of AI and ethical AI”, Journal of Database Management (JDM), 31(2): 74-87, (2020).
  • [26] Bleicher, J., Stanley, H., “Digitization as a catalyst for business model innovation a three-step approach to facilitating economic success”, Journal of Business Management, 12, (2017).
  • [27] Wong, Z. S., Zhou, J., Zhang, Q., “Artificial intelligence for infectious disease big data analytics”, Infection, Disease & Health, 24(1): 44-48, (2019).
  • [28] Hoffman, R. R., Mueller, S. T., Klein, G., Litman, J., “Metrics for explainable AI: Challenges and prospects”, arXiv preprint, arXiv:1812.04608, (2018).
  • [29] ElFar, O. A., Chang, C. K., Leong, H. Y., Peter, A. P., Chew, K. W., Show, P. L., “Prospects of Industry 5.0 in algae: Customization of production and new advance technology for clean bioenergy generation”, Energy Conversion and Management: X, 10: 100048, (2021).
  • [30] Walch, M., Karagiannis, D., “How to connect design thinking and cyber-physical systems: the s* IoT conceptual modelling approach”, In Proceedings of the 52nd Hawaii International Conference on System Sciences, (2019).
  • [31] Paschek, D., Mocan, A., Draghici, A., “Industry 5.0-The expected impact of next Industrial Revolution. In Thriving on Future Education, Industry, Business, and Society”, Proceedings of the MakeLearn and TIIM International Conference, Piran, Slovenia, 15-17, (2019).
  • [32] Moufaddal, M., Benghabrit, A., Bouhaddou, I., “Industry 4.0: A roadmap to digital Supply Chains”, In 2019 1st International Conference on Smart Systems and Data Science (ICSSD), 1-9, IEEE, (2019).
  • [33] Johnson, C. W., “The increasing risks of risk assessment: On the rise of artificial intelligence and non-determinism in safety-critical systems”, In the 26th Safety-Critical Systems Symposium, 15, Safety-Critical Systems Club York, UK, (2018).
  • [34] Nahavandi, S., “Robot-based motion simulators using washout filtering: Dynamic, immersive land, air, and sea vehicle training, vehicle virtual prototyping, and testing”, IEEE Systems, Man, and Cybernetics Magazine, 2(3): 6-10, (2016).
  • [35] Melnyk, L. H., Kubatko, O. V., Dehtyarova, I. B., Dehtiarova, I. B., Matsenko, O. M., Rozhko, O. D., “The effect of industrial revolutions on the transformation of social and economic systems”, Problems and Perspectives in Management, 17(4): 381-391, (2019).
  • [36] Welfare, K. S., Hallowell, M. R., Shah, J. A., Riek, L. D., “Consider the human work experience when integrating robotics in the workplace”, In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction, IEEE, 75-84, (2019).
  • [37] Saiz-Rubio, V., Rovira-Más, F., “From smart farming towards agriculture 5.0: A review on crop data management”, Agronomy, 10(2): 207, (2020).
  • [38] Sambasivam, G., Opiyo, G. D., “A predictive machine learning application in agriculture: Cassava disease detection and classification with imbalanced dataset using convolutional neural networks”, Egyptian Informatics Journal, 22(1): 27-34, (2021).
  • [39] Slayer, K. M., “Artificial Intelligence and National Security”, Congressional Research SVC Washington United States, (2020).
  • [40] Krause, P. J., Bokinala, V., “A Tutorial on Data Mining for Bayesian Networks, with a specific focus on IoT for Agriculture”, Internet of Things, 100738, (2023).
  • [41] Yıldırım, S., Jothimani, D., Kavaklioğlu, C., Başar, A., “Deep learning approaches for sentiment analysis on financial microblog dataset”, In 2019 IEEE International Conference on Big Data (Big Data), 5581-5584, IEEE, (2019).
  • [42] Rosa, M., Beloborodko, A., “Assessment and system analysis of industrial waste management”, Journal of Cleaner Production, 1, e10, (2014).
  • [43] Parr, M. K., Schmidt, A. H., “Life cycle management of analytical methods”, Journal of Pharmaceutical and Biomedical Analysis, 147, 506-517, (2018).
  • [44] Law, K., Stuart, A., Zygalakis, K., “Data assimilation”, Cham, Switzerland: Springer, 214, 52, (2015).
  • [45] Sherer, J. A., Le, J., Taal, A., “Big Data Discovery, Privacy, and the Application of Differential Privacy Mechanisms”, The Computer & Internet Lawyer, 32(7): 10-17, (2015).
  • [46] Tikkinen-Piri, C., Rohunen, A., Markkula, J., “EU General Data Protection Regulation: Changes and implications for personal data collecting companies”, Computer Law & Security Review, 34(1): 134-153, (2018).
  • [47] Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., Janowski, T., “Data governance: Organizing data for trustworthy Artificial Intelligence”, Government Information Quarterly, 37(3): 101493, (2020).
  • [48] Moret-Bonillo, V., “Can artificial intelligence benefit from quantum computing”, Progress in Artificial Intelligence, 3(2): 89-105, (2015).
  • [49] Akhtar, M. W., Hassan, S. A., Ghaffar, R., Jung, H., Garg, S., Hossain, M. S., “The shift to 6G communications: vision and requirements”, Human-centric Computing and Information Sciences, 10(1): 1-27, (2020).
  • [50] Khiadani, N., “Vision, Requirements and Challenges of Sixth Generation (6G) Networks”, In 2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), IEEE, 1-4, (2020).
  • [51] Kim, J., “Advertising in the Metaverse: Research agenda”, Journal of Interactive Advertising, 21(3): 141-144, (2021).
  • [52] Makori, E. O., “Blockchain Applications and Trends That Promote Information Management”, In Emerging Trends and Impacts of the Internet of Things in Libraries, 34-51, IGI Global, (2020).
  • [53] Seletsky, S., “The Good, the Bad, and the Inevitable About Industrial Revolution. IoT Practitioner”, https://iotpractitioner.com/the-good-the-bad-and-the-inevitable-about-industrial-revolution/. Access date: 25.02.2023
  • [54] Wang, W., Siau, K., “Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: A review and research agenda”, Journal of Database Management (JDM), 30(1): 61-79, (2019).
There are 54 citations in total.

Details

Primary Language English
Subjects Artificial Intelligence (Other)
Journal Section Review Article
Authors

Deepti Raj G 0000-0003-4640-6914

Prabadevi Boopathy 0000-0002-4075-1517

Early Pub Date October 1, 2024
Publication Date
Published in Issue Year 2025 Early View

Cite

APA G, D. R., & Boopathy, P. (2024). A Survey on AI Integration into Industry 5.0. Gazi University Journal of Science1-1. https://doi.org/10.35378/gujs.1320760
AMA G DR, Boopathy P. A Survey on AI Integration into Industry 5.0. Gazi University Journal of Science. Published online October 1, 2024:1-1. doi:10.35378/gujs.1320760
Chicago G, Deepti Raj, and Prabadevi Boopathy. “A Survey on AI Integration into Industry 5.0”. Gazi University Journal of Science, October (October 2024), 1-1. https://doi.org/10.35378/gujs.1320760.
EndNote G DR, Boopathy P (October 1, 2024) A Survey on AI Integration into Industry 5.0. Gazi University Journal of Science 1–1.
IEEE D. R. G and P. Boopathy, “A Survey on AI Integration into Industry 5.0”, Gazi University Journal of Science, pp. 1–1, October 2024, doi: 10.35378/gujs.1320760.
ISNAD G, Deepti Raj - Boopathy, Prabadevi. “A Survey on AI Integration into Industry 5.0”. Gazi University Journal of Science. October 2024. 1-1. https://doi.org/10.35378/gujs.1320760.
JAMA G DR, Boopathy P. A Survey on AI Integration into Industry 5.0. Gazi University Journal of Science. 2024;:1–1.
MLA G, Deepti Raj and Prabadevi Boopathy. “A Survey on AI Integration into Industry 5.0”. Gazi University Journal of Science, 2024, pp. 1-1, doi:10.35378/gujs.1320760.
Vancouver G DR, Boopathy P. A Survey on AI Integration into Industry 5.0. Gazi University Journal of Science. 2024:1-.