With the acceleration of urbanization, garbage production continues to increase, and garbage classification has become a key link in solving environmental problems. This paper designs an intelligent garbage classification system based on STM32. Through the comprehensive application of hardware selection and circuit design, software algorithm development and energy consumption optimization strategy, efficient and accurate garbage classification function is realized. In terms of hardware, STM32F103C8T6 is selected as the main control chip, and OV5640 camera module, GP2Y0A02YK0F infrared sensor, HC-SR04 ultrasonic sensor, MG90S servo and 28BYJ-48 stepper motor and other components are used to build a stable and reliable system architecture. In software design, after the garbage classification algorithm based on image recognition is optimized, the classification accuracy rate reaches 92%, and the average response time is 1.8 seconds. At the same time, through hardware circuit optimization and software algorithm improvement, the system standby power consumption is only 80 milliwatts, and the working power consumption is controlled below 4.5 watts. Experimental results show that the system can effectively reduce energy consumption, improve the accuracy and efficiency of garbage classification, and has good application prospects.

Xie Jiahui. Design and Energy Consumption Optimization of Intelligent Garbage Classification System Based on STM32. Academic Journal of Engineering and Technology Science (2025), Vol. 8, Issue 3: 59-66. https://doi.org/10.25236/AJETS.2025.080309.

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