The DOI matches its Crossref record; 92 of the 94 references it cites were found in a registry or an index.
Edge computing for Industry 5.0: fundamental, applications and research challenges
Abstract
Industry 5.0 is the next stage in industrial evolution, collaborating between human ingenuity and intelligent technologies to provide manufacturing solutions. Integrating modern technology like Artificial Intelligence (AI), robotics, and the Internet of Things (IoT) into manufacturing and production processes characterizes Industry 5.0. On the other hand, edge computing provides real-time data processing and analysis at the networks edge, closer to the data source and a vital component of Industry 5.0. Edge computing enables Industry 5.0 to access and communicate information about their industrial sectors using more accessible, standard hardware and software resources. However, no recent survey papers have examined the importance of edge computing in Industry 5.0. This study aims to fill that gap by presenting a survey on the importance of edge computing in Industry 5.0 and discussing a variety of technologies that could be used to implement and support this new industrial paradigm. First, we outline an overview and fundamentals of edge computing in Industry 5.0 architecture. Then objectives of Industry 5.0 are summarized to address various research challenges, including privacy, human-robot co-working, sustainability, and robust networks. Afterwards, this paper provides an extensive overview of emerging technologies for Industry 5.0, such as collaborative robots, AI, Digital Twins, and many more. In addition, this survey highlights various open research challenges and potential solutions that should be addressed further to achieve Industry 5.0.
Overview
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“These three fundamental objectives are resilience, sustainability, and human-centricity [71].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [71]
In the citing paper
“According to the study conducted by Sharma et al. [10], edge computing reduces latency and facilitates real-time decision-making.”
From Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework (2024) · cites this paper as [10]
Citations
Cites
Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications
Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2444095 · Cited by 8,630 · cited 1×
“It increases customer satisfaction and loyalty and creates customized experiences using data supplied by IoE [61].”
Industry 4.0: state of the art and future trends
Xu, L. D., Xu, E. L., & Li, L. (2018) · International Journal of Production Research · doi:10.1080/00207543.2018.1444806 · Cited by 3,405
The expected contribution of Industry 4.0 technologies for industrial performance
Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018) · International Journal of Production Economics · doi:10.1016/j.ijpe.2018.08.019 · Cited by 2,201
Chowdhury, M. Z., Shahjalal, M. A., Ahmed, S., & Jang, Y. M. (2020) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2020.3010270 · Cited by 1,925
Industry 5.0: A survey on enabling technologies and potential applications
Maddikunta, P. K. R., Pham, Q.-V., B, P., Deepa, N., Dev, K., Gadekallu, T. R., Ruby, R., & Liyanage, M. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2021.100257 · Cited by 1,890
Lu, Y., Liu, C., Wang, K. I., Huang, H., & Xu, X. W. (2019) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2019.101837 · Cited by 1,753
A Survey on Metaverse: Fundamentals, Security, and Privacy
Wang, Y., Su, Z., Zhang, N., Xing, R., Liu, D., Luan, T. H., & Shen, X. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3202047 · Cited by 1,655
6G Wireless Communications: Vision and Potential Techniques
Yang, P., Xiao, Y., Xiao, M., & Li, S. (2019) · IEEE Network · doi:10.1109/mnet.2019.1800418 · Cited by 1,153
Survey on fog computing: architecture, key technologies, applications and open issues
Hu, P., Dhelim, S., Ning, H., & Qiu, T. (2017) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2017.09.002 · Cited by 880
Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook
Peres, R. S., Jia, X., Lee, J., Sun, K., Colombo, A. W., & Barata, J. (2020) · IEEE Access · doi:10.1109/access.2020.3042874 · Cited by 820
Research works printed but not linked: 5
- Hasegawa, Industrial wireless standardization—Scope and implementation of ISA SP100 standard, 2059
- Mattila, 2022, The fifth industrial revolution: Enlightenment of 5ire towards industry 5.0, Int. J. Creat. Res. Thoughts, 10, 178
- 10.1016/j.ecmx.2020.100048 · DOI
- Breque, 2021, Industry 5.0: Towards a Sustainable, Human-Centric and Resilient European Industry
- Van der Valk, A taxonomy of digital twins, 1
Cited by
Sorted by citations
Edge Computing and Cloud Computing for Internet of Things: A Review
Andriulo, F. C., Fiore, M., Mongiello, M., Traversa, E., & Zizzo, V. (2024) · Informatics · doi:10.3390/informatics11040071 · Cited by 249
Islam, M. T., Sepanloo, K., Woo, S., Woo, S. H., & Son, Y. (2025) · Machines · doi:10.3390/machines13040267 · Cited by 193
Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework
Sathupadi, K., Achar, S., Bhaskaran, S. V., Faruqui, N., Abdullah-Al-Wadud, M., & Uddin, J. (2024) · Sensors · doi:10.3390/s24247918 · Cited by 89
“According to the study conducted by Sharma et al. [10], edge computing reduces latency and facilitates real-time decision-making.”
Rijwani, T., Kumari, S., Srinivas, R., Abhishek, K., Iyer, G., Vara, H., Dubey, S., Revathi, V., & Gupta, M. (2024) · International Journal on Interactive Design and Manufacturing (IJIDeM) · doi:10.1007/s12008-024-01943-7 · Cited by 85
Addula, S. R. (2025) · Journal of theoretical and applied electronic commerce research · doi:10.3390/jtaer20030192 · Cited by 63
Metadata
- Authors
- Sharma, M., Tomar, A., & Hazra, A.
- Affiliations
- Netaji Subhas University of Technology (IN)
- Indian Institute of Information Technology Sri City (IN)
- Venue
- IEEE Internet of Things Journal
- Published
- 2024-06-01
- Volume
- 11
- Issue
- 11
- Pages
- 19070-19093
- ISSN
- 2327-4662 (ISSN-L)
- 2372-2541
- OpenAlex
- W4392543840
- Cited by
- 312
- References
- 94
- Citations by year
- 2026: 117 · 2025: 161 · 2024: 34
- FWCI
- 51.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Internet of Things Journal (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Data and IoT Technologies
- Keywords
- edge computing, Industry 5.0, manufacturing industry, collaborative robots, digital twin, artificial intelligence in manufacturing, Internet of Things, privacy, sustainability, network robustness, real-time data processing
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