Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture - Saha Laboni; Dubey Ahilya (SHS Web of Conferences)
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.