On optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plots

Q4 Agricultural and Biological Sciences Biulleten'' Pochvennogo instituta im VV Dokuchaeva Pub Date : 2022-06-25 DOI:10.19047/0136-1694-2022-110-22-50
I. Savin, Y. Blokhin
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引用次数: 1

Abstract

One of the main stream of digitalization in agriculture is the introduction of Internet of Things technologies, which is expressed in the creation and use of specialized sensors that are placed in the fields. The placement of such sensors within agricultural plot should make it possible to characterize all the microvariability of soil fertility parameters in the field. That is, their number and spatial location should be optimal, on the one hand, in terms of costs of their acquisition and operation, and, on the other hand, in terms of accuracy of interpolation of data obtained with their help to the entire plot. It has been shown that the use of crop condition maps obtained on the basis of satellite data and the separation based on them of management zones can lead to significant errors in the interpolation of monitoring results, obtained in separate points, on the whole plot. An approach for optimization of sensor placement is proposed based on the use of soil fertility mapping, which is the result of refinement, updating and clarification of traditionally drawn soil maps on the basis of high spatial resolution remote sensing data. The possibilities of using the approach are demonstrated by the example of a test plot in Leningrad region of Russia. 
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优化物联网传感器网络在耕地土壤和作物监测中的部署
农业数字化的主流之一是物联网技术的引入,这表现为在田地里创建和使用专门的传感器。将这种传感器放置在农田中,应该可以表征田地中土壤肥力参数的所有微变量。也就是说,它们的数量和空间位置应该是最优的,一方面,就它们的获取和操作成本而言,另一方面,在它们对整个绘图的帮助下获得的数据的插值精度而言。已经表明,使用根据卫星数据获得的作物状况图,并根据这些数据划分管理区,可能会导致在整个地块上对单独点获得的监测结果的插值出现重大误差。提出了一种基于土壤肥力图的传感器布局优化方法,该方法是在高空间分辨率遥感数据的基础上对传统绘制的土壤图进行细化、更新和澄清的结果。以俄罗斯列宁格勒地区的一个试验区为例,说明了使用该方法的可能性。
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
15
审稿时长
8 weeks
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