Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture

Water scarcity poses a big challenge to modern agriculture that needs artificial solutions to make water efficient and sustainable. The objective of this research is to explore the use of advanced artificial intelligence (AI) technologies for creating smart irrigation system to enhance water efficacy in agriculture. The proposed AI solutions are integrated platform of machine learning algorithms and sensor data, predictive analytics for the purpose to generate a water efficient irrigation framework reacts dynamically to the crops' needs and environmental conditions. A multi-faceted approach will be used in the study that takes the form of the development of AI driven models for predicting soil moisture levels, weather patterns and crop water requirements. Their performance will be validated through real field trials in the real world, and they will be compared with traditional practices. The research will also integrate IoT sensors and automated control system to automate irrigation scheduling and distribution, and increase the precision of irrigation. Outcomes that are expected include reduction in water consumption, better crop productivity and sustainability of agricultural practices. Finding will help progress of smart agriculture technologies for the benefit of farmers, policy makers and researchers. This research is in the context of addressing the larger objectives of addressing global water challenges as well as contributing to sustainable agricultural practices with technological innovations.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-05-23
DOI
https://doi.org/10.1051/shsconf/202521601052/pdf
Primary Topic
Smart Agriculture and AI
Type
article
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article

Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture

Ahilya Dubey, Laboni Saha
Springer Link (Chiba Institute of Technology)
Smart Agriculture and AI
article

Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture

Ahilya Dubey, Laboni Saha
article en

Abstract

Water scarcity poses a big challenge to modern agriculture that needs artificial solutions to make water efficient and sustainable. The objective of this research is to explore the use of advanced artificial intelligence (AI) technologies for creating smart irrigation system to enhance water efficacy in agriculture. The proposed AI solutions are integrated platform of machine learning algorithms and sensor data, predictive analytics for the purpose to generate a water efficient irrigation framework reacts dynamically to the crops' needs and environmental conditions. A multi-faceted approach will be used in the study that takes the form of the development of AI driven models for predicting soil moisture levels, weather patterns and crop water requirements. Their performance will be validated through real field trials in the real world, and they will be compared with traditional practices. The research will also integrate IoT sensors and automated control system to automate irrigation scheduling and distribution, and increase the precision of irrigation. Outcomes that are expected include reduction in water consumption, better crop productivity and sustainability of agricultural practices. Finding will help progress of smart agriculture technologies for the benefit of farmers, policy makers and researchers. This research is in the context of addressing the larger objectives of addressing global water challenges as well as contributing to sustainable agricultural practices with technological innovations.

Springer Link (Chiba Institute of Technology)
Zero hunger
Openalex Percentile: Top 21%
Smart Agriculture and AI
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Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture — Ahilya Dubey, Laboni Saha · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS