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A Temporal Learning Framework: From Experience of Artificial Cultivation to Knowledge

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Book cover Green, Pervasive, and Cloud Computing (GPC 2018)

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Abstract

This paper presents a novel learning framework to generate fine-grained temporal cultivation knowledge from large climatic sensor data. Compared with human-experience based control, the machine-learned cultivation knowledge can provide precise climatic descriptions in temporal domain during the growth of plants. In the paper, the temporal characteristics of the sensor data are analyzed with heat maps in different temporal aspects. A merging algorithm on temporal segments, which are initialized with respect to the regularity of the heat maps, is designed to create climatic labels. Then the training samples consisting of temporal attributes and climatic labels are constructed for knowledge learning, which is represented as a collection of tree-structured classifiers. The experiments are carried out on the cultivation of a valuable Chinese herbal medicine. A cultivation knowledge cube in month, day and hour dimensions is illustrated. The results show that about 80% climatic conditions in the past successful cases can be duplicated to guide the future artificial cultivation by our method. The framework can also be applied to learn the knowledge of cultivation practices for other plants.

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Acknowledgment

The authors would like to thank Prof. Yong He of Zhejiang University for providing the sensor data. This work is supported by Zhejiang Provincial Natural Science Foundation of China (No. LY17F020008), Hangzhou Science and Technology Development Plan Project (No. 20150432B17, 20162012A06, 20170432B30).

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Authors and Affiliations

  1. Intelligent Plant Factory of Zhejiang Province Engineering Lab, Zhejiang University City College, Hangzhou, China

    Lin Sun, Zengwei Zheng & Jianzhong Wu

  2. College of Computer Science and Technology, Zhejiang University, Hangzhou, China

    JianFeng Zhu

Authors
  1. Lin Sun
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  2. Zengwei Zheng
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  3. Jianzhong Wu
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  4. JianFeng Zhu
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Corresponding author

Correspondence to Lin Sun .

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Editors and Affiliations

  1. Zhejiang University, Hangzhou, China

    Shijian Li

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Sun, L., Zheng, Z., Wu, J., Zhu, J. (2019). A Temporal Learning Framework: From Experience of Artificial Cultivation to Knowledge. In: Li, S. (eds) Green, Pervasive, and Cloud Computing. GPC 2018. Lecture Notes in Computer Science(), vol 11204. Springer, Cham. https://doi.org/10.1007/978-3-030-15093-8_30

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  • DOI: https://doi.org/10.1007/978-3-030-15093-8_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15092-1

  • Online ISBN: 978-3-030-15093-8

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