基于UWB与物联网的移动式温室环境监测系统设计与实现

侯加林; 蒲文洋; 李天华; 丁小明; 张观山

doi:10.11975/j.issn.1002-6819.2020.23.027

基于UWB与物联网的移动式温室环境监测系统设计与实现

1.
山东农业大学机械与电子工程学院，泰安 271018
2.
山东省农业装备智能化工程实验室，泰安 271018
3.
农业农村部规划设计研究院设施农业研究所，北京 100125

基金项目: 十三五国家重点研发计划项目智能农机装备专项"温室智能化精细生产技术与装备研发"（2017YFD0701500）；山东省重大科技创新工程项目（2019JZZY020620）

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出版历程
- 收稿日期: 2020-09-08
- 修回日期: 2020-10-26
- 发布日期: 2020-11-30

Design and implementation of mobile greenhouse environmental monitoring system based on UWB and Internet of Things

1.
College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian 271018, China
2.
Shandong Provincial Engineering Laboratory of Agricultural Equipment Intelligence, Taian 271018, China
3.
Institute of Protected Agriculture, Academy of Agricultural Planning and Engineering, Ministry of Agriculture and Rural Affaires, Beijing 100125, China

摘要

摘要: 为低成本实现对温室不同区域环境的全面感知，该研究设计了移动式温室环境监测系统，其采用超宽带（Ultra Wide Band，UWB）网状拓扑结构进行分布式组网，节点设备以一主多从的形式对移动工作台实时定位。利用优化后的双向双边测距算法计算各基站与标签之间的距离，通过距离的归一化残差分布判断是否存在非视距（Non Line of Sight, NLOS）误差，利用改进后的增量卡尔曼滤波算法消除NLOS误差，通过Chan算法解算标签准确位置。移动工作台以Arduino控制器为核心，搭载温度、湿度、二氧化碳和光照度传感器，实现对温室环境的实时监测和对移动工作台的远程控制。测试结果表明，系统静态定位最大横向偏差为7.92 cm，最大纵向偏差为7.98 cm，横向和纵向偏差的平均值均<5 cm；移动工作台以0.4 m/s的平均速度行驶，动态定位最大横向偏差为8.7 cm，平均横向偏差为4.7 cm；采集参数上传平均丢包率为2.78%；温度、湿度、光照度和二氧化碳浓度监测相对误差分别低于0.63%、0.34%、0.70%和0.67%，满足温室环境信息移动监测要求。该研究对温室环境调控和温室内作业机具精准定位技术的发展具有一定的理论意义和参考价值。
- 温室 /
- 环境调控 /
- 物联网 /
- UWB /
- 移动工作台 /
- 定位
Abstract: To grasp timely and conveniently environmental information such as temperature and humidity in the greenhouse, a mobile greenhouse environment monitoring system was designed, which realized the mobile monitoring of greenhouse environmental parameters. According to the improved double-side-two-way-ranging algorithm, the distance between each base station and the tag was calculated. The NLOS error was judged by the normalized residual distribution of distance, and the improved incremental Kalman filter algorithm was used to eliminate the NLOS error, and the Chan algorithm was used to calculate the accurate tag position. The mobile greenhouse environment monitoring system was composed of a remote monitoring platform, mobile workstation, and UWB positioning module. The remote monitoring platform was responsible for displaying the location information of the mobile workstation in real-time, controlling the movement of the mobile workstation remotely, displaying and storing the environmental information uploaded by the environmental information monitoring module. Mobile workstation mainly included mobile chassis, drive module, control module, environmental information measurement module, UWB positioning label, and communication module. As the specific executor of the command, the mobile workstation was responsible for receiving and executing the mobile command issued by the monitoring platform, collecting and sending the measured temperature and humidity and other environmental parameters to the monitoring platform in real-time. The remote monitoring platform and the mobile workstation communicate timely through the wireless network. The UWB positioning module included a positioning tag, positioning base station, and a computing unit. The positioning tag was installed on the mobile workstation to mark the position of the mobile workstation in the greenhouse. The positioning base station was responsible for calculating the distance between each base station and the tag and sending it to the computing unit by serial communication. The computing unit calculated the position of the tag in the greenhouse and displays it. The software of the environmental monitoring system consisted of a position information interaction layer, environment information monitoring layer, and motion control layer. The position information interaction layer was a real-time positioning program based on windows, which displayed the position of a mobile workstation in the greenhouse. The environmental information monitoring layer was an Android-based program to collect and display environmental information measured by sensors, drawing the hourly temperature and humidity change curve. The motion control layer was an Android-based remote control program, which sent motion instructions to the mobile workstation through the remote communication protocol to control the stable and safe movement of the mobile workstation in the greenhouse. The remote control and positioning accuracy-test showed that the maximum lateral deviation of the system static positioning was 7.92 cm, the maximum longitudinal deviation was 7.98 cm, and the average value of both horizontal and longitudinal deviation was less than 5 cm. When the mobile workstation was running at a speed of 0.4 m/s, the maximum lateral deviation of dynamic positioning was 8.7 cm and the average lateral deviation was 4.7 cm. Through the stability test of environmental information collection, the average data loss rate of the collected greenhouse environmental parameters uploaded to the remote monitoring platform was 2.78%, the environmental information collection was stable. The relative errors of temperature, humidity, light intensity and carbon dioxide concentration were less than 0.63%, 0.34%, 0.70%, and 0.67%, respectively, the environmental monitoring accuracy was high. The system adopted modular hardware structure design and layered software structure design, taking into account the requirements of the system for data through flux and response speed. Combined with the remote monitoring platform, it realized remote control, precise positioning, and remote real-time monitoring of the greenhouse environment. The system could have certain reference significance for the development of remote environmental monitoring technology and greenhouse precise positioning technology.
- greenhouse /
- environmental control /
- Internet of Thing /
- UWB /
- mobile workstation /
- location

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