<![CDATA[An infant incubator is a critical life-support device that provides thermal regulation for premature or low-birth-weight infants who are unable to maintain stable body temperature. Precise temperature control is essential, as instability and prolonged transient responses can increase health risks. Conventional on-off control methods commonly used in basic incubator systems often result in slower stabilization and higher temperature error. Therefore, this study aims to design and implement a baby incubator temperature control system using a fuzzy logic controller (FLC) integrated with a DS18B20 temperature sensor to improve thermal stability. The proposed system was implemented on a physical incubator prototype and evaluated experimentally. System performance was assessed based on dynamic response characteristics, including rise time, peak overshoot, and settling time. Experiments were conducted using three temperature setpoints: 32°C, 35°C, and 36°C. To ensure measurement accuracy, system performance was validated using an Incu Analyzer as a reference device. The experimental results show that the fuzzy logic-based control system achieved a steady-state temperature error of approximately 1% across all setpoints. The maximum observed settling time after peak overshoot was 100 seconds, indicating faster and more stable temperature regulation compared with conventional on-off control methods reported in previous studies. These results demonstrate that fuzzy logic control is effective in handling nonlinear thermal dynamics and improving temperature stability in infant incubator systems. This study focuses on technical performance evaluation; therefore, further investigations related to safety assessment and regulatory compliance are required before clinical implementation. Nevertheless, the proposed system shows strong potential as an intelligent temperature control approach for the development of neonatal incubator technology.]]>
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