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International Conference on Machine Learning and Intelligent Communications

MLICOM 2017: Machine Learning and Intelligent Communications pp 33–42Cite as

Agricultural IoT System Based on Image Processing and Cloud Platform Technology

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Abstract

Detection of crop disease and growth state have always been the key to ensure the yield and quality of agricultural products. The algorithms, which are in the field of pattern recognition or image recognition, have been using to crop-disease detection and growth-state detection, these algorithms undoubtedly have great significance, and with the development of IoT technology in recent years, the Internet of things technology combining with the existing technology will be the future direction of intelligent agriculture. This paper proposed an agricultural system, which based on the image processing technology and cloud platform of the Internet of things technology. The system can complete image recognition process real-time detection and recording of crop growth status and alarm crop disease in time based on the mutual connection with the cloud platform, and truly realize the unmanned detection in the field of intelligent agricultural system.

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Authors and Affiliations

  1. Communication Research Center, Harbin Institute of Technology, Harbin, 150001, China

    Yaxin Zheng & Chungang Liu

Authors
  1. Yaxin Zheng
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  2. Chungang Liu
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Corresponding author

Correspondence to Yaxin Zheng .

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Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Xuemai Gu

  2. Harbin Institute of Technology, Weihai, Heilongjiang, China

    Gongliang Liu

  3. Shandong University, Weihai, Heilongjiang, China

    Bo Li

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Cite this paper

Zheng, Y., Liu, C. (2018). Agricultural IoT System Based on Image Processing and Cloud Platform Technology. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73447-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-73447-7_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73446-0

  • Online ISBN: 978-3-319-73447-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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