Towards sustainable industry 4.0: A survey on greening IoE in 6G networks

Authors

  • Saeed Hamood Alsamhi Insight Centre for Data Analytics, University of Galaway, Ireland Faculty of Engineering, IBB University, 70270, Ibb, Yemen Department of Computer Science and Engineering, College of Informatics, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea Corresponding author at: Insight Centre for Data Analytics, University of Galaway, Ireland. Author https://orcid.org/0000-0003-2857-6979
  • Ammar Hawbani School of Computer Science, Shenyang Aerospace University, Shenyang 110136, China Author
  • Radhya Sahal Computer Science, Hudida University, Hudida Ibb, Yemen Author
  • Sumit Srivastava Department of Electronics and Communication Engineering, FET, MJP Rohilkhand University, Bareilly, Uttar Pradesh 243006, India Author
  • Santosh Kumar Department of CSE, IIIT Naya Raipur, Chhattisgarh, India Author
  • Liang Zhao School of Computer Science, Shenyang Aerospace University, Shenyang 110136, China Author
  • Mohammed A A Al-Qaness Emirates International University image/svg+xml Author
  • Jahan Hassan School of Engineering and Technology, College of ICT, Central Queensland University, Australia Author https://orcid.org/0000-0002-0939-2106
  • Mohsen Guizani Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, United Arab Emirates Author
  • Edward Curry Insight Centre for Data Analytics, University of Galaway, Ireland Author https://orcid.org/0000-0001-8236-6433

DOI:

https://doi.org/10.1016/j.adhoc.2024.103610

Keywords:

6G , Connectivity , Energy efficiency , Green IoE , Industry 4.0 , Sustainability

Abstract

The dramatic recent increase of the smart Internet of Everything (IoE) in Industry 4.0 has significantly increased energy consumption, carbon emissions, and global warming. IoE applications in Industry 4.0 face many challenges, including energy efficiency, heterogeneity, security, interoperability, and centralization. Therefore, Industry 4.0 in Beyond the Sixth-Generation (6G) networks demands moving to sustainable, green IoE and identifying efficient and emerging technologies to overcome sustainability challenges. Many advanced technologies and strategies efficiently solve issues by enhancing connectivity, interoperability, security, decentralization, and reliability. Greening IoE is a promising approach that focuses on improving energy efficiency, providing a high Quality of Service (QoS), and reducing carbon emissions to enhance the quality of life at a low cost. This survey provides a comprehensive overview of how advanced technologies can contribute to green IoE in the 6G network of Industry 4.0 applications. This survey provides a comprehensive overview of advanced technologies, including Blockchain, Digital Twins (DTs), Unmanned Aerial Vehicles (UAVs, a.k.a. drones), and Machine Learning (ML), to improve connectivity, QoS, and energy efficiency for green IoE in 6G networks. We evaluate the capability of each technology in greening IoE in Industry 4.0 applications and analyse the challenges and opportunities to make IoE greener using the discussed technologies.

Author Biographies

  • Saeed Hamood Alsamhi, Insight Centre for Data Analytics, University of Galaway, Ireland Faculty of Engineering, IBB University, 70270, Ibb, Yemen Department of Computer Science and Engineering, College of Informatics, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea Corresponding author at: Insight Centre for Data Analytics, University of Galaway, Ireland.
    Saeed Hamood Alsamhi received an M.Tech. degree in communication systems and a Ph.D. degree from the Department of Electronics Engineering, Indian Institute of Technology (Banaras Hindu University), IIT (BHU), Varanasi, India, in 2012 and 2015. In 2009, he worked as a Lecturer Assistant in the Engineering faculty at IBB University. Afterward, he held a postdoctoral position with the School of Aerospace Engineering, Tsinghua University, Beijing, China. Since 2019, he has been an Assistant Professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen. In 2020, he worked as MSCA SMART 4.0 FELLOW at Athlone Institute of Technology, Athlone, Ireland. Currently, he is a Senior Research Fellow, at Insight Centre for Data Analytics, University of Galway, Ireland; Adjunct Professor at the Department of Computer Science and Engineering, College of Informatics, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea; and Assistant Professor at Faculty of Engineering, IBB University, Ibb, Yemen. His areas of interest include green and semantic communication, green Internet of Things, QoE, QoS, Cybersecurity, multi-robot collaboration, blockchain technology, federated learning, and space technologies (high altitude platforms, drones, and tethered balloon technologies).
  • Ammar Hawbani, School of Computer Science, Shenyang Aerospace University, Shenyang 110136, China
    Ammar Hawbani received the B.S., M.S. and Ph.D. degrees in computer software and theory from the University of Science and Technology of China (USTC), Hefei, China, in 2009, 2012, and 2016, respectively. He served as a Post-Doctoral Researcher and an Associate Researcher at the School of Computer Science and Technology, USTC, from 2016 to 2023. Currently, He is a Full Professor with the School of Computer Science, Shenyang Aerospace University. His research interests include the IoT, WSNs, WBANs, WMNs, VANETs and SDN.
  • Radhya Sahal, Computer Science, Hudida University, Hudida Ibb, Yemen
    Radhya Sahal is a SMART 4.0 Research Fellow in Confirm Centre for Smart Manufacturing, University College Cork. She has received her M.Sc. and Ph.D. in computer science in 2013 and 2018 from Faculty of Computers and Information, Cairo University, Egypt respectively. Radhya has publications in the area of Big Data, Cloud Database, IoT, Industry 4.0 and Healthcare. Her research interests include Big Data, Blockchain, Stream Processing, Query Optimization over large-scale distributed data systems, Internet of Things (IoT), Industry 4.0, Digital Twins, Smart Manufacturing and Smart Cities.
  • Sumit Srivastava, Department of Electronics and Communication Engineering, FET, MJP Rohilkhand University, Bareilly, Uttar Pradesh 243006, India
    Sumit Srivastava Sumit Srivastava received the Ph.D. from Indian Institute of Technology (B.H.U.), Varanasi. He has more than 18 years of teaching experience. He is working as Assistant Professor (Senior Scale) in the Department of Electronics and Communication Engineering, FET, MJP Rohilkhand University Bareilly, INDIA. He has Published more than 30 research Papers in different reputed Journals and Conferences. His research interests include, IoT, Artificial Intelligence, Machine Learning, Smart Sensors, Microstrip Patch Antennas and Federated Learning.
  • Santosh Kumar, Department of CSE, IIIT Naya Raipur, Chhattisgarh, India
    Santosh Kumar is an Assistant Professor in Computer Science and Engineering discipline. Prior to joining IIIT-NR, Dr. Santosh Kumar was a Ph.D. scholar in the Department of Computer Science and Engineering, IIT (B.H.U.), Varanasi, Uttar Pradesh, India. He is an active member of the Computer Society and the Association for Computing Machinery. He has published over 14 journal (SCI-index journal) and 5 conference papers (including 2 tier-1 international conferences (ACM multimedia-2016 and Mobisys-2016); filed 1patent, and 14 book chapters in edited books (Springer publication and IGI publication).
  • Liang Zhao, School of Computer Science, Shenyang Aerospace University, Shenyang 110136, China
    Liang Zhao (Member, IEEE) is a Professor at Shenyang Aerospace University, China. He received his Ph.D. degree from the School of Computing at Edinburgh Napier University in 2011. Before joining Shenyang Aerospace University, he worked as associate senior researcher in Hitachi (China) Research and Development Corporation from 2012 to 2014. He is also a JSPS invitational Fellow (2023) and a visiting professor at the University of Electro- Communications, Japan. He was listed as Top 2% of scientists in the world by Standford University (2022 and 2023). His research interests include ITS, VANET, WMN and SDN.
  • Mohammed A A Al-Qaness , Emirates International University
    Mohammed A. A. Al-qaness received the B.S., M.S., and Ph.D. degrees from Wuhan University of Technology, in 2010, 2014, and 2017, respectively, all in information and communication engineering. He was an Assistant Professor with the School of Computer Science, Wuhan University. He was also a Postdoc Researcher at the State Key Laboratory for Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University. Now, he is a Professor at the College of Physics and Electronic Information Engineering, Zhejiang Normal University. His current research interests include Wi-Fi sensing, wireless sensing, mobile computing, machine learning, signal and image processing, and natural language processing.
  • Jahan Hassan, School of Engineering and Technology, College of ICT, Central Queensland University, Australia
    Jahan Hassan a Senior Lecturer at the Central Queensland University, holds a PhD from the University of New South Wales and a Bachelor’s degree from Monash University, Australia, both in Computer Science. She is an Area Editor for Elsevier’s Ad Hoc Networks and has guest-edited for IEEE Communications Magazine, Elsevier Ad Hoc Networks, and IEEE Network. Dr. Hassan has published in top journals like IEEE Journal on Selected Areas in Communications and IEEE Transactions on Mobile Computing and has edited a book on machine learning in drone networks. Her research focuses on civilian applications of drones, IoT, and AI, including leading a grant-funded project on AI-assisted weed management. A Senior Member of the IEEE and a Certified Professional Member of ACS, she has served on Technical Program Committees for over 30 international conferences. Dr. Hassan champions women in technology, co-chairing the N2Women initiative at IEEE WoWMoM 2024 and chairing the Women in Technology workshop at IEEE ITNAC 2020. Additionally, she is a co-chair of the 2024 DroneSense-AI workshop.
  • Mohsen Guizani, Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, United Arab Emirates
    Mohsen Guizani is currently a Professor of Machine Learning at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, UAE. His research interests include applied machine learning, artificial intelligence, Internet of Things, smart city, and cybersecurity. He was elevated to the IEEE Fellow in 2009 and was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science in 2019, 2020 and 2021.
  • Edward Curry, Insight Centre for Data Analytics, University of Galaway, Ireland
    Edward Curry is the Established Professor of Data Science and Director of the Insight SFI Research Centre for Data Analytics at the University of Galway. Edward has made substantial contributions to semantic technologies, incremental data management, event processing middleware, software engineering, as well as distributed systems and information systems. He combines strong theoretical results with high-impact practical applications. The excellence and impact of his research have been acknowledged by numerous awards, including best paper awards and the University of Galway President’s Award for Societal Impact in 2017. His team’s technology enables intelligent systems for smart environments in collaboration with several industrial partners. He is organizer and programme co-chair of major international conferences, including CIKM 2020, ECML 2018, IEEE Big Data Congress, and European Big Data Value Forum. Edward is co-founder and elected Vice President of the Big Data Value Association, an industry-led European big data community, has built consensus on a joint European big data research and innovation agenda, and influenced European data innovation policy to deliver on the agenda.

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How to Cite

Alsamhi, S. H., Hawbani, A., Sahal, R., Srivastava, S., Kumar, S., Zhao, L., Al-qaness, M. A., Hassan, J., Guizani, M., & Curry, E. (2024). Towards sustainable industry 4.0: A survey on greening IoE in 6G networks. Emirates International University Digital Repository, 1(1). https://doi.org/10.1016/j.adhoc.2024.103610

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