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  Published Paper Details:

  Paper Title

Atmospheric Water Harvesting System with smart irrigation integration

  Authors

  Madhuri P. Narkhede,  Pratibha Sharma,  Jayotsna Thakur,  Nitu Rajbhar

  Keywords

Machine Learning, IoT, Agriculture, Smart Irrigation.

  Abstract


The growing pressures of climate change, water scarcity, and the need for sustainable agricultural practices have driven significant research into smart irrigation and machine learning-based solutions. Agriculture, as one of the most water-intensive sectors, faces the dual challenge of maximizing crop yields while minimizing resource consumption. Recent advancements in sensor technologies, Internet of Things (IoT) systems, predictive analytics, and atmospheric water harvesting have enabled data-driven approaches to irrigation management, offering precise control over water delivery based on real-time environmental and crop conditions. Machine learning, in particular, has emerged as a transformative tool, enabling accurate predictions of soil moisture, evapotranspiration, and rainfall patterns, as well as adaptive decision-making for diverse agricultural contexts.

  IJCRT's Publication Details

  Unique Identification Number - IJCRTBI02003

  Paper ID - 296912

  Page Number(s) - 12-18

  Pubished in - Volume 13 | Issue 12 | December 2025

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Madhuri P. Narkhede,  Pratibha Sharma,  Jayotsna Thakur,  Nitu Rajbhar,   "Atmospheric Water Harvesting System with smart irrigation integration", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 12, pp.12-18, December 2025, Available at :http://www.ijcrt.org/papers/IJCRTBI02003.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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