Issue |
E3S Web Conf.
Volume 131, 2019
2nd International Conference on Biofilms (ChinaBiofilms 2019)
|
|
---|---|---|
Article Number | 01117 | |
Number of page(s) | 5 | |
DOI | https://doi.org/10.1051/e3sconf/201913101117 | |
Published online | 19 November 2019 |
Preliminary Study on Data Fusion Based on Internet of Things of Eucalyptus Plantation
1
Research Institute of Forest Resource Information Techniques, China Academy of Forestry Sciences, 100091 Beijing, China
2
Suzhou Yingchuang Kyushu Information Technology Co., Ltd., Suzhou, China
* Corresponding author: javawsdp@sina.com
Eucalyptus is the main fast-growing and high-yielding tree species in southern China and is the main source of wood production. Over the years, there have been many reports that eucalyptus is a water pump and that eucalyptus causes serious damage to understory vegetation. In this paper, a sensor network of eucalyptus plantation has been established in Yinling branch of Gaofeng Forest Farm in Guangxi, the main eucalyptus producing province. The sensor network can monitor the DBH changes, trunk runoff, soil moisture, environmental information and so on of eucalyptus in the stand in real time. The collected data are uploaded to the artificial forest Internet of Things monitoring information cloud management system established in this paper. This paper introduces the functions of the cloud management system in detail. On this basis, this paper discusses the fusion of high-frequency information collected from monitoring points to meet different data requirements. The research on data fusion in this paper is very preliminary. In the conclusion part, the future research on long-term monitoring data fusion of eucalyptus forest is prospected.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.