EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 216 (2025) SHS Web Conf., 216 (2025) 01022 References
Open Access
Issue
SHS Web Conf.
Volume 216, 2025
International Conference on the Impact of Artificial Intelligence on Traditional Economic Sectors (ICIAITES 2025)
Article Number 01022
Number of page(s) 11
Section Intelligent Systems and Digital Transformation in Agricultural Economy and Sustainable Development
DOI https://doi.org/10.1051/shsconf/202521601022
Published online 23 May 2025
  1. X. Zhang, Z. Cao, W. Dong, Overview of edge computing in the agricultural internet of things: Key technologies, applications, challenges. IEEE Access 8, 141748–141761 (2020). https://doi.org/10.1109/ACCESS.2020.3013247 [CrossRef] [Google Scholar]
  2. C. Centofanti, W. Tiberti, A. Marotta, F. Graziosi, D. Cassioli, Taming latency at the edge: A user-aware service placement approach. Comput. Netw. 247, 110444 (2024). https://doi.org/10.1016/j.comnet.2024.110444 [CrossRef] [Google Scholar]
  3. Z. Chang, S. Liu, X. Xiong, Z. Cai, G. Tu, A survey of recent advances in edge-computingpowered artificial intelligence of things. IEEE Internet Things J. 8(18), 13849–13875 (2021). https://doi.org/10.1109/JIOT.2021.3072318 [CrossRef] [Google Scholar]
  4. O. Friha, M.A. Ferrag, L. Shu, L. Maglaras, X. Wang, Internet of things for the future of smart agriculture: A comprehensive survey of emerging technologies. IEEE/CAA J. Autom. Sinica 8(4), 718–752 (2021). https://doi.org/10.1109/JAS.2021.1003925 [CrossRef] [Google Scholar]
  5. A.A. AlZubi, K. Galyna, Artificial intelligence and internet of things for sustainable farming and smart agriculture. IEEE Access 11, 78686–78692 (2023). https://doi.org/10.1109/ACCESS.2023.3295428 [CrossRef] [Google Scholar]
  6. A. Sengupta, S.S. Gill, A. Das, D. De, Mobile edge computing based internet of agricultural things: a systematic review and future directions. Mobile Edge Computing, 415–441 (2021). https://doi.org/10.1007/978-3-030-69893-5_17 [CrossRef] [Google Scholar]
  7. R. Gomathi, S. Gopalakrishnan, S.R. Chand, S. Selvakumaran, J.J. Gracewell, B. Kalivaraprasad, Design and Speed Analysis of Low Power Single and Double Edge Triggered Flip Flop with Pulse Signal Feed-Through Scheme. IJEER (to be published) [Google Scholar]
  8. R.K. Singh, R. Berkvens, M. Weyn, AgriFusion: An architecture for IoT and emerging technologies based on a precision agriculture survey. IEEE Access 9, 136253–136283 (2021). https://doi.org/10.1109/ACCESS.2021.3116488 [CrossRef] [Google Scholar]
  9. J. Han, L. Qiao, Q. Zhang, Edge computing in precision agriculture: Case studies and future directions. Comput. Electron. Agric. 202, 107340 (2023). https://doi.org/10.1016/j.compag.2022.107340 [Google Scholar]
  10. S. Premkumar, A.N. Sigappi, IoT-enabled edge computing model for smart irrigation system. J. Intell. Syst. 31(1), 632–650 (2022). https://doi.org/10.1515/jisys-2022-0046 [Google Scholar]
  11. R. Zhang, X. Li, Edge computing driven data sensing strategy in the entire crop lifecycle for smart agriculture. Sensors 21(22), 7502 (2021). https://doi.org/10.3390/s21227502 [CrossRef] [Google Scholar]
  12. X. Zhang, Z. Cao, W. Dong, Overview of edge computing in the agricultural internet of things: Key technologies, applications, challenges. IEEE Access 8, 141748–141761 (2020). https://doi.org/10.1109/ACCESS.2020.3013247 [CrossRef] [Google Scholar]
  13. W. Zhang, Y. Liu, K. Chen, H. Li, Y. Duan, W. Wu, W. Guo, Lightweight fruit-detection algorithm for edge computing applications. Front. Plant Sci. 12, 740936 (2021). https://doi.org/10.3389/fpls.2021.740936 [CrossRef] [Google Scholar]
  14. M.U. Safder, M.J. Sanjari, A. Hamza, R. Garmabdari, M.A. Hossain, J. Lu, Enhancing microgrid stability and energy management: Techniques, challenges, and future directions. Energies 16(18), 6417 (2023). https://doi.org/10.3390/en16186417 [CrossRef] [Google Scholar]
  15. R. Wang, J. Lai, Z. Zhang, X. Li, P. Vijayakumar, M. Karuppiah, Privacy-preserving federated learning for internet of medical things under edge computing. IEEE J. Biomed. Health Inform. 27(2), 854–865 (2022). https://doi.org/10.1109/JBHI.2022.3159548 [Google Scholar]
  16. E.K. Ruby, G. Amirthayogam, G. Sasi, T. Chitra, A. Choubey, S. Gopalakrishnan, Advanced Image Processing Techniques for Automated Detection of Healthy and Infected Leaves in Agricultural Systems. Mesop. J. Comput. Sci. 2024, 62–70 (2024). https://doi.org/10.40052/mjcs.v2024i1.444 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.