A Mobile Greenhouse Environment Monitoring System Based on the Internet of Things

A knowledge of the environmental information of different spaces of large greenhouse is a prerequisite for effective control, and multipoint monitoring is therefore needed. In view of the problems of current greenhouse environmental monitoring, a mobile greenhouse environment monitoring system was d...

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Bibliographic Details
Main Authors: Xia Geng, Qinglei Zhang, Qinggong Wei, Tong Zhang, Yu Cai, Yong Liang, Xiaoyong Sun
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8839049/
Description
Summary:A knowledge of the environmental information of different spaces of large greenhouse is a prerequisite for effective control, and multipoint monitoring is therefore needed. In view of the problems of current greenhouse environmental monitoring, a mobile greenhouse environment monitoring system was designed based on the Internet of Things. A four-layer system architecture with outstanding motion control functions was constructed that uses mobile acquisition rather than multiple sensing nodes to realize the automatic collection of greenhouse environmental information and capture pictures of the crops with low cost. In this study, a Raspberry Pi and an Arduino chip were combined for the first time in agriculture greenhouse environmental monitoring, with the former serving as the data server and the latter as the master chip for the mobile system. Firstly, the application layer server was deployed on the Raspberry Pi, secondly, due to its compact size and stable performance, Raspberry Pi and sensors etc. were all integrated into the mobile system, shortening the physical distance between the data acquisition end and the data processing end, and serial communication was used. In addition, a dedicated communication protocol with Cyclic Redundancy Check (CRC) checking was designed to reduce data loss at the transmission layer. The data was denoised using a limiting filtering algorithm and a weighted average filtering algorithm to improve quality of the data. The experimental results show that the system can effectively realize multi-point environmental monitoring of the greenhouse.
ISSN:2169-3536