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All issues Volume 216 (2025) SHS Web Conf., 216 (2025) 01002 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 01002
Number of page(s) 12
Section Intelligent Systems and Digital Transformation in Agricultural Economy and Sustainable Development
DOI https://doi.org/10.1051/shsconf/202521601002
Published online 23 May 2025
  1. K. Kansotia, R. Naresh, Y. Sharma, M. Sekhar, P. Sachan, K. Baral, S.K. Pandey, Nanotechnology-driven Solutions: Transforming agriculture for a sustainable and productive future. J. Sci. Res. Rep. 30, 32–51 (2024). http://article.researchpromo.com/id/eprint/2155/ [CrossRef] [Google Scholar]
  2. M.E. Bekri, O. Diouri, D. Chiadmi, Dynamic Inertia Weight Particle Swarm Optimization for Anomaly Detection: A Case of Precision Irrigation. J. Internet Serv. Inf. Secur. 13, 157–176 (2023) [Google Scholar]
  3. H. Wen, C. Liu, Effect of the interlayer construction on the performances of the TFC-FO membranes: A review from materials perspective. Desalination 541, 116033 (2022) [CrossRef] [Google Scholar]
  4. T. Robles, R. Alcarria, D.M. De Andrés, M.N. De la Cruz, R. Calero, S. Iglesias, M. Lopez, An IoT based reference architecture for smart water management processes. J. Wirel. Mob. Netw. Ubiquitous Comput. Dependable Appl. 6, 4–23 (2015) [Google Scholar]
  5. S. Manikandan, R. Subbaiya, M. Saravanan, M. Ponraj, M. Selvam, A. Pugazhendhi, A critical review of advanced nanotechnology and hybrid membrane based water recycling, reuse, and wastewater treatment processes. Chemosphere 289, 132867 (2022) [CrossRef] [PubMed] [Google Scholar]
  6. A. Bozkurt, Investigation of Groundwater Zooplankton Fauna from Water Wells in Kilis Province from Türkiye. Nat. Eng. Sci. 8, 86–105 (2023) [Google Scholar]
  7. A. Hatami-Marbini, S. Hekmat, P.J. Agrell, A strategy-based framework for supplier selection: A grey PCA-DEA approach. Oper. Res. 22, 263–297 (2022). https://doi.org/10.1007/s12351-020-00556-8 [Google Scholar]
  8. S. Ravichandran, S. Vivekanandhan, Scientometric analysis of waste water management research publications from scopus database during 2010-2019. Libr. Philos. Pract., 1–17 (2021) [Google Scholar]
  9. S. Mohammed, J. Aburabie, R. Hashaikeh, A review on the potential of cellulose nanomaterials for the development of thin film composite polyamide membranes for water treatment. Chemosphere, 142927 (2024) [CrossRef] [Google Scholar]
  10. J. Cevallos-Mendoza, C.G. Amorim, J.M. Rodríguez-Díaz, M.D.C.B. Montenegro, Removal of contaminants from water by membrane filtration: a review. Membranes 12, 570 (2022) [CrossRef] [Google Scholar]
  11. N.N.R. Ahmad, A.W. Mohammad, E. Mahmoudi, W.L. Ang, C.P. Leo, Y.H. Teow, An overview of the modification strategies in developing antifouling nanofiltration membranes. Membranes 12, 1276 (2022) [CrossRef] [Google Scholar]
  12. T.U. Rahman, H. Roy, M.R. Islam, M. Tahmid, A. Fariha, A. Mazumder, M.S. Islam, The advancement in membrane bioreactor (MBR) technology toward sustainable industrial wastewater management. Membranes 13, 181 (2023) [CrossRef] [Google Scholar]
  13. N. Sohail, R. Riedel, B. Dorneanu, H. Arellano-Garcia, Prolonging the life span of membrane in submerged MBR by the application of different anti-biofouling techniques. Membranes 13, 217 (2023) [CrossRef] [Google Scholar]
  14. R.L. Robinson, Investigating Biofouling on Long-Term, In Situ, Optic Sensors: Impacts on Optical Measurement Integrity and Insight Into Community Dynamics, Master Thesis, University of Windsor, Canada (2024) [Google Scholar]
  15. M.S. Sheela, S.R. Chand, S. Gopalakrishnan, M. Gopianand, J.J. Hephzipah, Empowering Aquarists a Comprehensive Study On IOT-Enabled Smart Aquarium Systems For Remote Monitoring And Control. Babylon. J. Internet Things, 33–43 (2024) [CrossRef] [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. Mesopotamian J. Comput. Sci., 62–70 (2024) [Google Scholar]
  17. S. Zhang, L. Shen, H. Deng, Q. Liu, X. You, J. Yuan, S. Zhang, Ultrathin membranes for separations: a new era driven by advanced nanotechnology. Adv. Mater. 34, 2108457 (2022) [CrossRef] [Google Scholar]
  18. N.A. Khan, S. Singh, E.A. López-Maldonado, N. Pavithra, P.F. Méndez-Herrera, J.R. López-López, I.H. Aljundi, Emerging membrane technology and hybrid treatment systems for the removal of micropollutants from wastewater. Desalination 565, 116873 (2023) [CrossRef] [Google Scholar]
  19. M. Tello, E.S. Reich, J. Puckey, R. Maff, A. Garcia-Arce, B.S. Bhattacharya, F. Feijoo, Machine learning based forecast for the prediction of inpatient bed demand. BMC Med. Inform. Decis. Mak. 22, 55 (2022). https://doi.org/10.1186/s12911-022-01787-9 [CrossRef] [Google Scholar]
  20. M.C. Garg, S. Kumari, N. Malik, Role of nanomaterials in advanced membrane technologies for groundwater purification. Environ. Sci.: Water Res. Technol. (2024) [Google Scholar]

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