<![CDATA[The cooling process of granular products requires stable temperature control to maintain material quality. Conventional chiller systems with manual control tend to produce significant temperature fluctuations and operate less efficiently. This study proposes a Raspberry Pi-based chiller control system using the fuzzy logic method to improve temperature stability and enable real-time monitoring through the Internet of Things (IoT). The system utilizes the DS18B20 sensor for temperature measurement and the DHT22 sensor for humidity measurement, with a Peltier TEC1-12706 module serving as the cooling actuator and a blower fan functioning as the humidity controller. The fuzzy logic method is applied to determine the cooling performance level based on the measured temperature conditions. The test results indicate that the system is capable of regulating temperature adaptively, with a measurement error of ±0.89% for the DS18B20 temperature sensor and ±3.33% for the DHT22 humidity sensor. The actuators operate according to the detected conditions, where the Peltier TEC1-12706 functions at three levels (maximum, medium, and off), while the blower fan is activated when the humidity exceeds 70%. The implementation of this system demonstrates improved temperature stability and control effectiveness compared to conventional methods, making it suitable for application in small- to medium-scale granular product cooling systems.]]>
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