Development of a Fuzzy Case-Based Reasoning Decision Support System for Water Management in Smart Agriculture

This paper proposes a decision support system aimed at improving water management in smart agriculture, utilizing the Case-Based Reasoning (CBR) methodology. Given the increasing challenges of water resources and the need for their optimal use in agriculture, the application of advanced technologies for smart resource management has gained significant importance. The proposed system assists in better decision-making regarding irrigation timing and quantity by collecting data from various sensors, including information about environmental conditions, soil status, and plant water needs. As part of the system, the case-based reasoning model uses historical data and similarity comparison between current situations and previous cases to offer optimal water management solutions. The Internet of Things (IoT), as the main infrastructure of this system, facilitates the continuous and real-time collection of data, thereby enhancing the accuracy of decisions. The results obtained show that this system can optimize water consumption, reduce irrigation costs, and increase agricultural productivity. The key findings of this study suggest that this approach could serve as a sustainable solution for water efficiency in smart agriculture and optimal water resource management in the future.