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首页> 中文期刊> 《农业工程学报》 >基于物联网的荔枝园信息获取与智能灌溉专家决策系统

基于物联网的荔枝园信息获取与智能灌溉专家决策系统

         
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摘要

In order to realize the real time remote monitoring and precise management of the environment in litchi orchard, an information acquisition and intelligent irrigation expert decision system based on Internet of things in litchi orchard was designed. The system collected real-time environmental information such as soil moisture, air temperature and humidity, light intensity, wind speed and rainfall of litchi orchard through information collecting terminal modules then transmitted data packets of environmental information to gateway through wireless sensor network. The data packets would be processed and then transmitted to the cloud server through the GPRS network by the gateway. Combined with the environmental data and expert knowledge, the expert-decision system would establish multiple mathematical models of decision to achieve some decision-making functions such as the crop water requirements computing, irrigation time prediction, optimum quantitative irrigation decision-making and irrigation scheduling. The decision results were fed back to the control terminal module for intelligent controlling. The system was tested at the litchi orchard of College of Horticulture in South China Agricultural University from Feb. 11th, 2016 to Mar. 15th, 2016. In the test of the monitoring accuracy of information collecting terminal module, the results obtained from TES-1317 resistance thermometer, DT-8896 wet and dry bulb hygrometer, AR813A light illumination measuring instrument and so on were compared with those obtained information collecting terminal module. The results revealed the maximum relative error of the temperature 2.98%, that of the humidity 3.06%, that of the illumination was 6.25%, that of soil moisture 4.13%, that of wind speed 4.76% and precipitation 2.25%. It indicated that the monitoring accuracy of information collecting terminal module was high and was able to provide precise decision-making data for expert decision system. The decision-making system with multi-parameter and single parameter was tested to measure the accuracy of the expert decision system and determine the accuracy of the system according to the comparison between drought condition and actual situation. The result showed that the accuracy of multi-parameter decision was higher than the simple single parameter decision. The system gained the number of days automatically during the tests of the decision-making instantaneity of the system. When the soil water content was lower than the minimum of the litchi optimum water content which was 15.55%, the system opened the solenoid valve and began to do drip irrigation. On the other hand, the system stopped doing drip irrigation when the soil water content was higher than 19.14%. The result showed that the average soil water content of irrigation area was 17.4%, satisfying the requirement of the soil water content in the growth process of litchi trees, which illustrated that the irrigation decision made by system had strong real-time. The result from subtracting the days interval for predicting irrigation of the system by the days when the soil water content was below the minimum from the system began to irrigate showed that the system prediction accuracy could reach 75%, which illustrated that the predicting real-time of the system was better. This system realizes environmental information acquisition and intelligent irrigation in litchi orchard, guiding the users manage the litchi orchard better.%为实现荔枝园环境的实时远程监控和精准管理，设计基于农业物联网的荔枝园信息获取与智能灌溉专家决策系统，该系统通过信息采集终端模块实时采集荔枝园的土壤含水率、空气温湿度、光照强度、风速和降雨量等环境信息，通过无线传感网将数据包发送到网关上，网关通过通用无线分组网（general packet radio service，GPRS）将处理后的数据包传输到云服务器，专家系统根据采集到的环境数据，结合专家知识，建立多个决策数学模型，实现计算作物需水量、预报灌溉时间、灌溉最佳定量决策、根据灌溉制度决策等决策功能，将决策结果反馈到控制终端模块进行智能监控。经试验，对比系统多参数决策和一般的单参数决策得出的结论，多参数决策的准确性更高；灌溉区域的土壤含水率平均值为17.4%，满足荔枝树生长所需的土壤含水率条件，说明系统的灌溉决策具有比较强的实时性。且系统预测能达到75%的准确率，说明系统的预测实时性比较好。该系统实现了荔枝园的环境信息获取与智能灌溉，能指导用户更好地管理荔枝园。

著录项

  • 来源
    《农业工程学报》 |2016年第20期|144-152|共9页
  • 作者

    余国雄; 王卫星; 谢家兴; 陆华忠; 林进彬; 莫昊凡;

  • 作者单位

    华南农业大学电子工程学院;

    广州 510642;

    广州市农情信息获取与应用重点实验室;

    广州 510642;

    华南农业大学电子工程学院;

    广州 510642;

    广州市农情信息获取与应用重点实验室;

    广州 510642;

    广东省农情信息监测工程技术研究中心;

    广州 510642;

    华南农业大学南方农业机械与装备关键技术省部共建教育部重点实验室;

    广州 510642;

    华南农业大学电子工程学院;

    广州 510642;

    广州市农情信息获取与应用重点实验室;

    广州 510642;

    广东省农情信息监测工程技术研究中心;

    广州 510642;

    华南农业大学南方农业机械与装备关键技术省部共建教育部重点实验室;

    广州 510642;

    华南农业大学南方农业机械与装备关键技术省部共建教育部重点实验室;

    广州 510642;

    华南农业大学工程学院;

    广州 510642;

    华南农业大学电子工程学院;

    广州 510642;

    华南农业大学电子工程学院;

    广州 510642;

  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 灌溉期和灌溉预报;灌溉系统;
  • 关键词

    灌溉; 决策; 无线传感器网络; 农业物联网; 荔枝园; 专家系统; 信息获取;

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