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All issues Volume 216 (2025) SHS Web Conf., 216 (2025) 01036 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 01036
Number of page(s) 11
Section Intelligent Systems and Digital Transformation in Agricultural Economy and Sustainable Development
DOI https://doi.org/10.1051/shsconf/202521601036
Published online 23 May 2025
  1. M.T. Gómez-Villarino, J. Urquijo, M. Gomez Villarino, A.I. García, Key insights of urban agriculture for sustainable urban development. Agroecol. Sustain. Food Syst. 45(10), 1441–1469 (2021). https://doi.org/10.1080/21683565.2021.1917471 [CrossRef] [Google Scholar]
  2. A. Radhika, M.S. Masood, Crop Yield Prediction by Integrating Et-DP Dimensionality Reduction and ABP-XGBOOST Technique. J. Internet Serv. Inf. Secur. 12(4), 177–196 (2022) [Google Scholar]
  3. M.H.M. Saad, N.M. Hamdan, M.R. Sarker, State of the art of urban smart vertical farming automation system: Advanced topologies, issues and recommendations. Electronics 10(12), 1422 (2021). https://doi.org/10.3390/electronics10121422 [CrossRef] [Google Scholar]
  4. K. Veerasamy, E.T. Fredrik, Intelligent Farming based on Uncertainty Expert System with Butterfly Optimization Algorithm for Crop Recommendation. J. Internet Serv. Inf. Secur. 13(4), 158–169 (2023) [Google Scholar]
  5. T. Nguyen, D. Clark, Robotic Arm Technology for Precision Agriculture. Robot. Autom. Lett. 7(1), 56–65 (2022) [Google Scholar]
  6. K. Veerasamy, E.J. Thomson Fredrik, Intelligence System towards Identify Weeds in Crops and Vegetables Plantation Using Image Processing and Deep Learning Techniques. J. Wirel. Mob. Netw. Ubiquitous Comput. Dependable Appl. 14(4), 45–59 (2023) [Google Scholar]
  7. M.H.M. Saad, N.M. Hamdan, M.R. Sarker, State of the art of urban smart vertical farming automation system: Advanced topologies, issues and recommendations. Electronics 10(12), 1422 (2021). https://doi.org/10.3390/electronics10121422 [CrossRef] [Google Scholar]
  8. P.Ş. Toraman, N. Ergün, B. Çalıcı, Some abiotic stress on growth and lipid peroxidation on wheat seedlings. Nat. Eng. Sci. 5(3), 144–154 (2020) [Google Scholar]
  9. R. Sapkota, M.D. Whiting, D. Ahmed, M. Karkee, Robotics for crop pollination: recent advances and future direction. Authorea Preprints (2024) [Google Scholar]
  10. S. Thanuskodi, Authorship Pattern and Collaborative Measures in Seed Technology Research: A Scientometric Analysis, in Exploring Digital Metrics in Academic Libraries (IGI Global Scientific Publishing, 2025), pp. 1–32 [Google Scholar]
  11. R.R.A. Siregar, K.B. Seminar, S. Wahjuni, E. Santosa, Vertical farming perspectives in support of precision agriculture using artificial intelligence: A review. Computers 11(9), 135 (2022). https://doi.org/10.3390/computers11090135 [CrossRef] [Google Scholar]
  12. P.K. Paul, R.R. Sinha, P.S. Aithal, B. Aremu, R. Saavedra, Agricultural Informatics: An Overview of Integration of Agricultural Sciences and Information Science. Indian J. Inf. Sources Serv. 10(1), 48–55 (2020) [Google Scholar]
  13. S. Pearson, T.C. Camacho-Villa, R. Valluru, O. Gaju, M.C. Rai, I. Gould, S. Brewer, E. Sklar, Robotics and autonomous systems for net zero agriculture. Curr. Robot. Rep. 3(2), 57–64 (2022). https://doi.org/10.1007/s43154-022-00077-6 [CrossRef] [Google Scholar]
  14. A.S. Chole, A.R. Jadhav, V. Shinde, Vertical farming: Controlled environment agriculture. Just Agric. 1, 249–256 (2021) [Google Scholar]
  15. S.H. Van Delden, M. SharathKumar, M. Butturini, L.J.A. Graamans, E. Heuvelink, M. Kacira, L.F.M. Marcelis, Current status and future challenges in implementing and upscaling vertical farming systems. Nat. Food 2(12), 944–956 (2021). https://doi.org/10.1038/s43016-021-00402-w [CrossRef] [Google Scholar]
  16. W. Liu, J. Zhou, T. Zhang, P. Zhang, M. Yao, J. Li, J. Hu, Key Technologies in Intelligent Seeding Machinery for Cereals: Recent Advances and Future Perspectives. Agriculture 15(1), 8 (2024). https://doi.org/10.3390/agriculture15010008 [CrossRef] [Google Scholar]
  17. S.J. Park, S.M. Lee, M.H. Oh, Y.S. Huh, H.W. Jang, Food quality assessment using chemoresistive gas sensors: achievements and future perspectives. Sustain. Food Technol. 2(2), 266–280 (2024) [CrossRef] [Google Scholar]
  18. D.I. Patrício, R. Rieder, Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review. Comput. Electron. Agric. 153, 69–81 (2018). https://doi.org/10.1016/j.compag.2018.08.001 [CrossRef] [Google Scholar]
  19. M.S. Mir, N.B. Naikoo, R.H. Kanth, F.A. Bahar, M.A. Bhat, A. Nazir, S.S. Mahdi, T.A. Ahngar, Vertical farming: The future of agriculture: A review. Pharma Innov. J. 11(2), 1175–1195 (2022) [Google Scholar]

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