The increasingly efficient use of inputs in agriculture is particularly related to effective water management. This paper presents the modeling and analysis of the farmed soil moisture levels using fuzzy logic in a drip irrigation framework that involves the use of FLC for moisture control. Based on this, the study will determine ways in which a system can be designed to minimize water savings, enhance production, while ensuring cost-benefit analysis, sustaining the ideal soil moisture levels. A fuzzy-logic management has been suggested to change irrigation rates in accordance with actual time SM data. The system has been model using MATLAB/Simulink, and FLC received information from the soil moisture sensors. chilly plants crop water requirements set 7.24 lit/sec, ETc 4.68 then kc value 0.9 calculated water requirements for 7 months 942 mm/month all stage working time sets 216 hr. during 65%, water use efficiency, fuzzy logic control used 85%, and water wastage reduced by 25 % improve quality crop product and irrigation efficiency. The results showed that the fuzzy logic-based system enhanced the water use efficiency and kept the soil moisture within the optimum range for crop growth. Further discussion is developed with respect to the flexibility of FLC in terms of management of the uncertainties of the soil moisture dynamics and scalability to larger agricultural settings. In the end, it becomes clear that fuzzy logic control serves as a strong tool for precision irrigation: adaptive, with its key performance metrics of water use efficiency, soil moisture variability, and irrigation frequency. Future studies should integrate this system with data in weather forecasting to realize even more precision in irrigation scheduling. Keywords: moisture control, Fuzzy logic, sensors, Crop water requirements, Agricultural automation.