Suppr超能文献

精准农业技术与实践:从考量到应用。

Precision Agriculture Techniques and Practices: From Considerations to Applications.

机构信息

National University of Science and Technology (NUST), School of Electrical Engineering and Computer Science, Islamabad 44000, Pakistan.

Department of Languages and Computer Sciences, Ada Byron Research Building, University of Málaga, 29016 Málaga, Spain.

出版信息

Sensors (Basel). 2019 Sep 2;19(17):3796. doi: 10.3390/s19173796.

Abstract

Internet of Things (IoT)-based automation of agricultural events can change the agriculture sector from being static and manual to dynamic and smart, leading to enhanced production with reduced human efforts. Precision Agriculture (PA) along with Wireless Sensor Network (WSN) are the main drivers of automation in the agriculture domain. PA uses specific sensors and software to ensure that the crops receive exactly what they need to optimize productivity and sustainability. PA includes retrieving real data about the conditions of soil, crops and weather from the sensors deployed in the fields. High-resolution images of crops are obtained from satellite or air-borne platforms (manned or unmanned), which are further processed to extract information used to provide future decisions. In this paper, a review of near and remote sensor networks in the agriculture domain is presented along with several considerations and challenges. This survey includes wireless communication technologies, sensors, and wireless nodes used to assess the environmental behaviour, the platforms used to obtain spectral images of crops, the common vegetation indices used to analyse spectral images and applications of WSN in agriculture. As a proof of concept, we present a case study showing how WSN-based PA system can be implemented. We propose an IoT-based smart solution for crop health monitoring, which is comprised of two modules. The first module is a wireless sensor network-based system to monitor real-time crop health status. The second module uses a low altitude remote sensing platform to obtain multi-spectral imagery, which is further processed to classify healthy and unhealthy crops. We also highlight the results obtained using a case study and list the challenges and future directions based on our work.

摘要

基于物联网(IoT)的农业事件自动化可以将农业领域从静态和手动转变为动态和智能,从而在减少人力投入的情况下提高产量。精准农业(PA)和无线传感器网络(WSN)是农业自动化的主要驱动力。PA 使用特定的传感器和软件来确保作物获得优化生产力和可持续性所需的一切。PA 包括从部署在田间的传感器中检索有关土壤、作物和天气状况的实际数据。从卫星或空中平台(有人或无人)获取作物的高分辨率图像,然后对其进行进一步处理,以提取用于提供未来决策的信息。在本文中,我们对农业领域的近程和远程传感器网络进行了回顾,并提出了一些考虑因素和挑战。该调查包括用于评估环境行为的无线通信技术、传感器和无线节点、用于获取作物光谱图像的平台、用于分析光谱图像的常见植被指数以及 WSN 在农业中的应用。作为概念验证,我们提出了一个案例研究,展示了如何实现基于 WSN 的 PA 系统。我们提出了一种基于物联网的智能解决方案,用于监测作物健康,该解决方案由两个模块组成。第一个模块是一个基于无线传感器网络的系统,用于实时监测作物健康状况。第二个模块使用低空遥感平台获取多光谱图像,然后对其进行处理以对健康和不健康的作物进行分类。我们还强调了使用案例研究获得的结果,并根据我们的工作列出了挑战和未来方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0bd/6749385/bf2403b6dc32/sensors-19-03796-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验