灌溉作物无线传感器网络信息提供研究进展

J. Ekanayake, C. Hedley
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引用次数: 16

摘要

目前用于近实时环境监测的连接传感器技术的进展正在改变向土地管理者提供信息的质量。“第三次工业革命”将数字传感器数据分析与自适应服务联系起来,旨在改变数据处理方式,为及时决策提供支持。需要这些信息来改进灌溉计划,因为全球粮食需求严重依赖灌溉,而全球淡水资源正在减少。以前,从业者使用视觉指标,不频繁的测量或预测水平衡模型来估计灌溉计划。视觉指示器和不频繁的测量是近似的,预测模型需要许多输入,因此可能的累积错误导致调度不准确。相比之下,无线传感器网络可以近实时地连续测量目标位置的土壤湿度,为精确灌溉调度和有效的淡水管理提供所需的特定地点信息。本文描述并比较了Crossbow、DigiMesh和LoRa系统的结构、构建和实现,这些系统通过智能手机和网页向从业者提供时空土壤水分状况和作物胁迫信息,以改善灌溉土地的管理。我们的研究发现,较新的LoRA系统比其他系统具有优势,特别是在平坦的土地上,最远的节点范围为bbb10 km,并且可以穿透茂密的植被的先进通信协议。DigiMesh和Crossbow系统的网状网络在丘陵地形中更受欢迎,可以在丘陵周围进行通信,并且可以轻松扩展网络。弩系统安装更简单,但对第三方传感器集成提出了困难。所有系统都允许我们跟踪土壤水力特性和作物胁迫的动态变化的能力逐步变化,以提高灌溉用水效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances in Information Provision from Wireless Sensor Networks for Irrigated Crops
Current advances in connected sensor technologies for near real-time environmental monitoring are transforming the quality of information provision to land managers. This “Third Industrial Revolution” that connects digital sensor data analytics with adaptive services aims to transform data processing for timely decision support. The information is needed to improve irrigation scheduling, because global demand for food relies heavily on irrigation and global freshwater resources are diminishing. Previously, practitioners used visual indicators, infrequent measurements or predictive water balance models to estimate irrigation schedules. Visual indicators and infrequent measurements are approximate, and predictive models require many inputs so that likely cumulative errors cause inaccuracies in scheduling. In contrast, wireless sensor networks enable near real-time continuous measurement of soil moisture at targeted positions providing the site-specific information required for precision irrigation scheduling and efficient freshwater management. This paper describes and compares the structure, build and implementation of Crossbow, DigiMesh, and LoRa systems to deliver information on spatio-temporal soil water status and crop stress to practitioners over smart phones and webpages to improve management of irrigated land. Our study found that the newer LoRA system has advantages over the other systems, especially on flat land, with furthest node range of >10 km and advanced communication protocols that can penetrate dense vegetation. The mesh networking of the DigiMesh and Crossbow systems was preferred in hilly terrain to communicate around hills, and allows easy expansion of the network. The Crossbow system is simpler to install but presents difficulties for third party sensor integration. All systems allowed a step change in our ability to track dynamic changes in soil hydraulic properties and crop stress, to improve irrigation water use efficiency.
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