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易瑞曼平台:通过云计算技术实现灌溉管理,提高农业可持续性。

Irriman Platform: Enhancing Farming Sustainability through Cloud Computing Techniques for Irrigation Management.

机构信息

Agronomic Engineering Department, Agronomic Engineering Technical School, Alfonso XIII Campus, Technical University of Cartagena, 30203 Cartagena, Spain.

Automation, Electrical Engineering and Electronic Technology Department, Industrial Engineering Technical School, Muralla del Mar Campus, Technical University of Cartagena, 30202 Cartagena, Spain.

出版信息

Sensors (Basel). 2021 Dec 29;22(1):228. doi: 10.3390/s22010228.

DOI:10.3390/s22010228
PMID:35009770
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8749527/
Abstract

Crop sustainability is essential for balancing economic development and environmental care, mainly in strong and very competitive regions in the agri-food sector, such as the Region of Murcia in Spain, considered to be the orchard of Europe, despite being a semi-arid area with an important scarcity of fresh water. In this region, farmers apply efficient techniques to minimize supplies and maximize quality and productivity; however, the effects of climate change and the degradation of significant natural environments, such as, the "Mar Menor", the most extent saltwater lagoon of Europe, threatened by resources overexploitation, lead to the search of even better irrigation management techniques to avoid certain effects which could damage the quaternary aquifer connected to such lagoon. This paper describes the Irriman Platform, a system based on Cloud Computing techniques, which includes low-cost wireless data loggers, capable of acquiring data from a wide range of agronomic sensors, and a novel software architecture for safely storing and processing such information, making crop monitoring and irrigation management easier. The proposed platform helps agronomists to optimize irrigation procedures through a usable web-based tool which allows them to elaborate irrigation plans and to evaluate their effectiveness over crops. The system has been deployed in a large number of representative crops, located along near 50,000 ha of the surface, during several phenological cycles. Results demonstrate that the system enables crop monitoring and irrigation optimization, and makes interaction between farmers and agronomists easier.

摘要

农业可持续性对于平衡经济发展和环境保护至关重要,尤其是在农业食品部门实力雄厚且极具竞争力的地区,例如西班牙穆尔西亚大区,该地区被誉为“欧洲果园”,尽管它是一个半干旱地区,淡水资源严重短缺。在该地区,农民采用高效技术来尽量减少供应并最大限度地提高质量和生产力;然而,气候变化的影响以及重要自然环境的退化,如欧洲最大的盐水泻湖“马略卡湖”,由于资源过度开发而受到威胁,这促使人们寻找更好的灌溉管理技术,以避免可能破坏与泻湖相连的第四纪含水层的某些影响。本文介绍了 Irriman 平台,这是一个基于云计算技术的系统,包括能够从各种农业传感器中获取数据的低成本无线数据记录器,以及一种用于安全存储和处理此类信息的新型软件架构,使作物监测和灌溉管理更加容易。该平台通过一个可用的基于网络的工具帮助农学家优化灌溉程序,使他们能够制定灌溉计划,并评估其对作物的有效性。该系统已经在近 50000 公顷的大面积代表性作物上部署,在多个物候周期中进行了部署。结果表明,该系统能够实现作物监测和灌溉优化,并使农民和农学家之间的互动更加容易。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/2fff4ec16100/sensors-22-00228-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/b5a6dfd11e01/sensors-22-00228-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/070966062468/sensors-22-00228-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/9f79fb8a1be8/sensors-22-00228-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/e375b4a11d17/sensors-22-00228-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/c9874ad38caf/sensors-22-00228-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/d3719767f2bd/sensors-22-00228-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/3ab36e638797/sensors-22-00228-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/46a7b45c0efc/sensors-22-00228-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/6f2f840a0b44/sensors-22-00228-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/185b17fa72e0/sensors-22-00228-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/207095cb03b1/sensors-22-00228-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/96a5e7d5062c/sensors-22-00228-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/b5a6dfd11e01/sensors-22-00228-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/8085f1bde297/sensors-22-00228-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/12000df3e541/sensors-22-00228-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/070966062468/sensors-22-00228-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/9f79fb8a1be8/sensors-22-00228-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/e375b4a11d17/sensors-22-00228-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/c9874ad38caf/sensors-22-00228-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/d3719767f2bd/sensors-22-00228-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/3ab36e638797/sensors-22-00228-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/46a7b45c0efc/sensors-22-00228-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/6f2f840a0b44/sensors-22-00228-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/185b17fa72e0/sensors-22-00228-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/207095cb03b1/sensors-22-00228-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/96a5e7d5062c/sensors-22-00228-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef94/8749527/2fff4ec16100/sensors-22-00228-g015.jpg

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