智能灌溉与作物健康预测

Md Owais Quadri, Mahmood farmaan, Md Anas, Praveen Ku Reshma Ghani
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引用次数: 0

摘要

全球清洁水资源的稀缺已经产生了对其最佳利用的需求,基于特定应用传感器的数据采集和智能处理的物联网(IoT)解决方案正在弥合网络和物理世界之间的差距。基于物联网的智能灌溉系统可以帮助实现精准农业景观中水资源的最佳利用。本文提出了一种基于开源技术的智能系统,该系统通过对土壤湿度、土壤温度、环境条件等地面参数的感知以及来自互联网的天气预报数据来预测农田的灌溉需求。该系统的智能是基于一种智能算法,该算法将感知到的数据与近期的降水、气温、湿度、紫外线等天气预报参数一起考虑。完整的系统已经开发并部署在试点规模,其中传感器节点数据通过网络服务在云端无线收集,基于网络的信息可视化和决策支持系统提供基于传感器数据和天气预报数据分析的实时信息洞察。本文介绍了该系统,并详细讨论了基于该算法的三周数据信息处理结果。系统功能齐全,预测结果令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Irrigation and Crop Health Prediction
The scarcity of clean water resources around the globe has generated a need for their optimum utilization Internet of Things (IoT) solutions, based on the application specific sensors’ data acquisition and intelligent processing are bridging the gaps between the cyber and physical world. IoT based smart irrigation systems can help in achieving optimum water-resource utilization in the precision farming landscape. This paper presents an open-source technology based smart system to predict the irrigation requirements of a field using the sensing of ground parameter like soil moisture soil temperature, and environmental conditions along with the weather forecast data from the Internet. The intelligence of the proposed system is based on a smart algorithm, which considers sensed data along with the weather forecast parameters like precipitation, air temperature, humidity, and UV for the near future. The complete system has been developed and deployed on a pilot scale, where the sensor node data is wirelessly collected over the cloud using web-services and a web-based information visualization and decision support system provides the real-time information-insights based on the analysis of sensors data and weather forecast data. The paper describes the system and discusses in detail the information processing results of three weeks data based on the proposed algorithm. The system is fully functional and the prediction results are very encouraging.
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