Title: Automatic regulation of valves for release of water based upon soil moisture availability in the root zone of the crop, using artificial intelligence, in a piped and micro irrigation network of irrigation system.. Category: Agriculture, FoodTech  Rural Development. Subcategory: Hardware. Organization: Ministry of Jal Shakti. Description: In modern agricultural practices, efficient water management plays a critical role in achieving optimal crop yields, conserving water resources, and maintaining ecological balance. However, existing irrigation systems often lack the precision required to deliver water tailored to the actual needs of crops, leading to water wastage, suboptimal plant growth, and environmental degradation. This problem is particularly pronounced in piped and micro irrigation networks, where traditional methods of manual control fail to adapt dynamically to varying soil moisture conditions within the root zone of crops. The core issue lies in the absence of an automated mechanism that can regulate the release of water based on realtime soil moisture availability. The inconsistency in water distribution and the inability to synchronize irrigation with crop water requirements result in detrimental outcomes for both the agricultural yield and water conservation efforts. To address this problem, there is a compelling need for an innovative solution that leverages artificial intelligence AI to enable the automatic regulation of valves for water release in piped and micro irrigation networks. By incorporating AIpowered soil moisture monitoring and decisionmaking processes, this solution aims to bridge the gap between water supply and crop demand, while also optimizing resource utilization and minimizing environmental impact. Key Challenges Dynamic Water Demand Crops have varying water requirements influenced by factors such as growth stage, weather conditions, and plant type. Developing an AI system capable of accurately predicting these dynamic water demands is a complex challenge. Realtime Data Integration Integrating realtime soil moisture data from multiple sensors across a field into a centralized AI system requires robust data collection, transmission, and processing mechanisms. Algorithm Precision Designing AI algorithms that can effectively analyze soil moisture data, historical trends, and other relevant parameters to make accurate decisions about water release timing and quantities. Valve Control Mechanism Developing an automated valve control mechanism that can respond swiftly and accurately to the AIs recommendations while considering the physical characteristics of the piped and micro irrigation network. Adaptability Ensuring that the AI system can adapt to changing environmental conditions, crop types, and variations in soil properties over time. UserFriendly Interface Designing a userfriendly interface that allows farmers and irrigation managers to monitor and intervene in the system as needed, while also trusting in the AIs autonomous decisions. Economic Viability Balancing the potential costs of implementing an AIdriven system with the expected benefits in terms of increased crop yield, water savings, and operational efficiency.