Wireless Personal Communications

, Volume 97, Issue 3, pp 4251–4263 | Cite as

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

  • Shi Shen
  • Zuorui Shen
  • Ming ZhaoEmail author


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.


Invasive alien plants Wireless sensor networks Hadoop Flaveria bidentis 



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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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.College of Information and Electrical EngineeringChina Agricultural UniversityBeijingChina
  2. 2.Academy of Disaster Reduction and Emergency ManagementBeijing Normal UniversityBeijingChina
  3. 3.Center for Geodata and Analysis, Faculty of Geographical ScienceBeijing Normal UniversityBeijingChina

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