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In view of the ‘difficult’ situation of trash front-end classification, this paper proposes a novel intelligent classification trash bin based on Internet of Things (IoT) technology. This trash bin uses both STM32C8T6 control module and K210 vision module to control the operation of the whole equipment. Firstly, the image of the trash bin is collected by the OV5642 camera. Secondly, the function of trash detection and classification can be realized by the K210 vision module. Finally, the recognition results are transmitted to the STM32C8T6 control module through the UART serial port in the form of data, which controls the motor module, ultrasonic module and buzzer module to achieve trash classification, compression crushing and other functions. The experimental results show that the average accuracy of trash recognition is more than 87%. Compared with the traditional smart trash bin, the hardware of our design is added with recyclable trash compression and kitchen waste crushing structure, and the software of our design is added with LCD display interface for providing a more reliable, efficient and low-cost solution for trash classification.

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Design and Research of Intelligent Sorting Trash Bin Based on IoT

  • 会议论文

  • 发表日期：

    2025年

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  • Yuxi Yang,
  • Yuanqiao Bi,
  • Fuxiang Jiang,
  • Zhongying Hu,
  • Weile Bai,
  • Qifang Liu,
  • Xi Hu

摘要

In view of the ‘difficult’ situation of trash front-end classification, this paper proposes a novel intelligent classification trash bin based on Internet of Things (IoT) technology. This trash bin uses both STM32C8T6 control module and K210 vision module to control the operation of the whole equipment. Firstly, the image of the trash bin is collected by the OV5642 camera. Secondly, the function of trash detection and classification can be realized by the K210 vision module. Finally, the recognition results are transmitted to the STM32C8T6 control module through the UART serial port in the form of data, which controls the motor module, ultrasonic module and buzzer module to achieve trash classification, compression crushing and other functions. The experimental results show that the average accuracy of trash recognition is more than 87%. Compared with the traditional smart trash bin, the hardware of our design is added with recyclable trash compression and kitchen waste crushing structure, and the software of our design is added with LCD display interface for providing a more reliable, efficient and low-cost solution for trash classification.