<![CDATA[Urban waste management systems often fail to address hygiene and efficiency when relying on conventional bins or rigid threshold-based controllers. This paper presents a low-cost smart trash bin that integrates dual-sensor fuzzy logic control to adaptively regulate lid positions in real time. Unlike prior designs dependent on a single sensing modality, the proposed system fuses odor intensity (via MQ-2 gas sensor) and fill-level data (via HY-SRF05 ultrasonic sensor) within a Sugeno-type fuzzy inference framework. The controller supports five graded lid positions, ranging from fully closed to fully open, ensuring nuanced and hygienic responses to varying environmental conditions. Experimental validation across 25 scenarios yielded robust performance, with maximum errors below 9% and an average deviation of only 1.91%. The most accurate results were observed in the fully closed state, while the highest deviations occurred in the almost closed position due to mechanical limitations and nonlinear actuator behavior. Despite these drawbacks, the system consistently demonstrated adaptive decision-making and stable operation, confirming its suitability for real-world applications. Furthermore, comparative analysis against threshold-based and AI-based controllers reveals that the fuzzy approach achieves superior adaptability and near-ANN accuracy while maintaining computational efficiency compatible with Arduino-based platforms. These findings establish fuzzy sensor fusion as a practical pathway toward sustainable, IoT-enabled, and educationally relevant waste management solutions, paving the way for integration into future smart city infrastructures]]>
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