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Big Data Monitoring System Design and Implementation of Invasive Alien Plants Based on WSNs and WebGIS

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Abstract

Invasive alien plants (IAPs) are an important reason for biodiversity crisis and changes of local ecosystem and landscape. The key content of IAPs investigating research is about how to timely and efficiently monitor the growth and occurrence of IAPs. Timely gathering IAPs’ occurrence is helpful for governments to prevent and control them in time. Moreover, in the Big data era, the increasing data of observation data has been a problem for researchers to understand the growth law and controlling efficiencies about IAPs. In this paper, an IAPs monitoring system based on WSNs and WebGIS is presented. This system can collect not only long-term and real-time environment information, but images of monitoring stations by WSNs. Google Maps and ArcGIS are used to display the WSNs and IAPs occurrence information. Especially, the Hadoop-based image processing interface is taken advantage of to process the big data acquired by this system. This system solves the problems about surveying IAPs (e.g., a single type of data and slow update rate). Since it has been already running since February 2012, continuous monitoring and evaluation of the long-term effect of the prevention and control methods about IAPs will be achieved as well.

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Acknowledgements

This work has been supported by the project entitled ‘Application and Promotion of the Monitoring and Management System of the Chinese Jujube Germplasm Resources’ by the institute of Shanxi Academy of agricultural sciences (2011 Special Funds of the IOT of MIIT). We gratefully acknowledge the cooperation and help of ‘Lvyuan’ Agricultural Science and Technology Co., Ltd., and ‘Hanjingjinhe’ Technology Co., Ltd. We would like to thank the anonymous reviewers for their invaluable comments.

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Authors and Affiliations

  1. College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, China

    Shi Shen, Zuorui Shen & Ming Zhao

  2. Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing, 100075, China

    Shi Shen

  3. Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University, Beijing, 100075, China

    Shi Shen

Authors
  1. Shi Shen
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  2. Zuorui Shen
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  3. Ming Zhao
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Correspondence to Ming Zhao.

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Shen, S., Shen, Z. & Zhao, M. Big Data Monitoring System Design and Implementation of Invasive Alien Plants Based on WSNs and WebGIS. Wireless Pers Commun 97, 4251–4263 (2017). https://doi.org/10.1007/s11277-017-4723-0

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  • DOI: https://doi.org/10.1007/s11277-017-4723-0

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