<![CDATA[This research investigates the critical necessity of microclimate regulation within broiler poultry housing by constructing a computational framework grounded in the Mamdani Fuzzy Inference System. Thermal fluctuations, relative humidity shifts, and ammonia accumulation are significantly correlated with poultry mortality rates. The proposed computational model acquires three input parameters (Temperature, Humidity, and Ammonia) to generate two decision variables (Fan Intensity and Coop Safety Status) through the evaluation of 27 logical rules. To ensure system reliability prior to hardware implementation on microcontrollers, the algorithm was validated using the MATLAB commercial simulator. The defuzzification process was executed utilizing the Center of Gravity (COG) approach, which was comparatively analyzed between theoretical mathematical calculations and software projections. The investigative results revealed a fundamental level of accuracy; manual computation recorded a value of 22.62, whereas the simulation instrument projected 22.60. The recorded margin of deviation was extremely reduced, standing at merely 0.088%. These findings confirm that the designed computational architecture is highly precise and strongly recommended for integration into Internet of Things (IoT) ecosystems for real-time agricultural automation.]]>
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