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Intelligent Garbage Classification System Based on Open MV

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Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1303))

Abstract

In the 20th century, the United Kingdom first implemented waste sorting and recycling, placing sorting barrels on the streets and recycling available resources. This method has also become popular worldwide. With the proposal of “smart city”, people have higher and higher requirements on quality of life, and the intelligentization of sorting buckets has become an inevitable trend. In order to respond to the call for garbage classification, this article has designed a set of intelligent garbage classification system based on STM32F103 Single-chip microcomputer, image processing technology and sensor technology. This article gives a more detailed and systematic description of the software framework and hardware design of the entire project. The design mainly uses the SSD algorithm and the Open MV module to identify and classify the types of garbage. The system controls the rotation of the steering gear baffle and the barrel in the garbage bin through the STM32F103 single-chip microcomputer, thereby performing accurate garbage classification. The intelligent trash can designed in this paper can realize the intelligent identification of garbage types and automatically complete the classification processing of garbage. In the future of the popularization of artificial intelligence, the design has certain innovative value, practical value and scientific research value.

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Acknowledgements

Fund project: innovation training project support for college students in Liaoning province (202012026167).

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Correspondence to Zhongfu Liu .

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Ma, H., Liu, Z., Zhai, Y. (2021). Intelligent Garbage Classification System Based on Open MV. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_1

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  • DOI: https://doi.org/10.1007/978-981-33-4572-0_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-4573-7

  • Online ISBN: 978-981-33-4572-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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