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@article{187691,
        author = {Kadar Shahajahan Tamboli and Dr.Dineshkumar U.Adokar},
        title = {AI-Enabled Intelligent Grid-Interface Solar Pumping System for Sustainable Water Management},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {6219-6221},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187691},
        abstract = {Rapid depletion of groundwater resources, unreliable grid availability, and rising energy demand have intensified the need for intelligent and sustainable irrigation technologies. Solar photovoltaic (PV) water pumping systems have emerged as a viable alternative; however, their performance is limited by intermittent solar irradiance, variable water demand, and inefficient control strategies. This paper proposes an AI-based intelligent grid-interface solar water pumping system that integrates machine learning (ML)–based predictive control, smart energy management, and grid-interactive functionality to optimize water extraction, maximize solar utilization, and ensure uninterrupted supply. Experimental simulations demonstrate improved pump efficiency, reduced grid dependency, and enhanced water resource sustainability. The proposed model is especially suitable for agricultural, rural, and semi-urban applications.},
        keywords = {AI-based irrigation, solar PV pumping, intelligent grid interface, smart water management, machine learning, sustainable agriculture, energy optimizations.},
        month = {November},
        }