Smart Decision System for Agricultural Water Use with AI and Environmental Data

Water scarcity has become one of the most critical challenges in Iran, especially in semi-arid regions where agriculture is a major consumer of water resources. Traditional irrigation methods and the absence of predictive tools have led to significant water waste and reduced agricultural productivity. This research aims to design a smart decision support system for optimizing agricultural water use by leveraging artificial intelligence (AI) and environmental data such as temperature, rainfall, humidity, and crop types. Using machine learning algorithms like Random Forest and Neural Networks, the system will analyze historical and real-time data to predict future water needs and provide farmers with personalized irrigation recommendations. The proposed solution contributes to sustainable agriculture and can serve as a model for smart water management in other regions of Iran.

کلیدواژه ها:

Artificial Intelligence ، Water Resource Management ، Smart Agriculture ، Decision Support System ، Data Mining ، Water Consumption Prediction ، Optimal Irrigation