The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Big data analysis of the Internet of Things in the digital twins of smart city based on deep learning
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Citations
Cites
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication
Huang, C., Zappone, A., Alexandropoulos, G. C., Debbah, M., & Yuen, C. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2922609 · Cited by 3,761
Digital twin: Enabling technologies, challenges and open research
Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020) · IEEE Access · doi:10.1109/access.2020.2998358 · Cited by 2,965
Brain tumor classification using deep CNN features via transfer learning
Deepak, S., & Ameer, P. M. (2019) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2019.103345 · Cited by 1,321
Machine Learning for Internet of Things Data Analysis: A Survey
Mahdavinejad, M. S., Rezvan, M., Barekatain, M., Adibi, P., Barnaghi, P. M., & Sheth, A. (2017) · Surrey Research Insight Open Access (The University of Surrey) · Cited by 1,008
Machine learning for internet of things data analysis: a survey
Mahdavinejad, M. S., Rezvan, M., Barekatain, M., Adibi, P., Barnaghi, P., & Sheth, A. P. (2018) · Digital Communications and Networks · doi:10.1016/j.dcan.2017.10.002 · Cited by 921
Digital Twins: The Convergence of Multimedia Technologies
El Saddik, A. (2018) · IEEE MultiMedia · doi:10.1109/mmul.2018.023121167 · Cited by 817
C2PS: A Digital Twin Architecture Reference Model for the Cloud-Based Cyber-Physical Systems
Alam, K. M., & El Saddik, A. (2017) · IEEE Access · doi:10.1109/access.2017.2657006 · Cited by 741
A digital twin smart city for citizen feedback
White, G., Zink, A., Codecá, L., & Clarke, S. (2021) · Cities · doi:10.1016/j.cities.2020.103064 · Cited by 548
Artificial intelligence and internet of things in small and medium-sized enterprises: A survey
Hansen, E. B., & Bøgh, S. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.08.009 · Cited by 407
Driver Activity Recognition for Intelligent Vehicles: A Deep Learning Approach
Xing, Y., Lv, C., Wang, H., Cao, D., Velenis, E., & Wang, F.-Y. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2908425 · Cited by 399
Cited by
Smart cities—a structured literature review
Gracias, J. S., Parnell, G. S., Specking, E., Pohl, E. A., & Buchanan, R. (2023) · Smart Cities · doi:10.3390/smartcities6040080 · Cited by 476
When Internet of Things Meets Metaverse: Convergence of Physical and Cyber Worlds
Li, K., Cui, Y., Li, W., Lv, T., Yuan, X., Li, S., Ni, W., Simsek, M., & Dressler, F. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3232845 · Cited by 266
Digital Twin for Civil Engineering Systems: An Exploratory Review for Distributed Sensing Updating
Bado, M. F., Tonelli, D., Poli, F., Zonta, D., & Casas, J. R. (2022) · Sensors · doi:10.3390/s22093168 · Cited by 158
Blockchain-based trust mechanism for digital twin empowered Industrial Internet of Things
A., S., Vairavasundaram, S., Kotecha, K., V., I., Ravi, L., Selvachandran, G., & Abraham, A. (2023) · Future Generation Computer Systems · doi:10.1016/j.future.2022.11.002 · Cited by 156
A comprehensive review of Digital Twin technologies in smart cities
Huzzat, A., Anpalagan, A., Khwaja, A. S., Woungang, I., Alnoman, A. A., & Pillai, A. S. (2025) · Digital Engineering · doi:10.1016/j.dte.2025.100040 · Cited by 65
Metadata
- Authors
- Li, X., Liu, H., Wang, W., Zheng, Y., Lv, H., & Lv, Z.
- Venue
- Future Generation Computer Systems
- Publisher
- Elsevier BV
- Published
- 2022-03
- Volume
- 128
- Pages
- 167-177
- ISSN
- 0167-739X (ISSN-L)
- OpenAlex
- W3207740732
- Cited by
- 398
- References
- 33
- FWCI
- 31.59
- Type
- journal article
- Language
- en
- Open access
- closed
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- Li, X., Liu, H., Wang, W., Zheng, Y., Lv, H., & Lv, Z. (2022). Big data analysis of the Internet of Things in the digital twins of smart city based on deep learning. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2021.10.006
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
