• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

基于微服务和云范式的畜牧业物联网平台。

An Internet of Things Platform Based on Microservices and Cloud Paradigms for Livestock.

机构信息

Department of Computer Science and Industrial Engineering, University of Lleida, 25001 Lleida, Spain.

Department of Business Administration, University of Lleida, 25001 Lleida, Spain.

出版信息

Sensors (Basel). 2021 Sep 4;21(17):5949. doi: 10.3390/s21175949.

DOI:10.3390/s21175949
PMID:34502840
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8434670/
Abstract

With the growing adoption of the Internet of Things (IoT) technology in the agricultural sector, smart devices are becoming more prevalent. The availability of new, timely, and precise data offers a great opportunity to develop advanced analytical models. Therefore, the platform used to deliver new developments to the final user is a key enabler for adopting IoT technology. This work presents a generic design of a software platform based on the cloud and implemented using microservices to facilitate the use of predictive or prescriptive analytics under different IoT scenarios. Several technologies are combined to comply with the essential features-scalability, portability, interoperability, and usability-that the platform must consider to assist decision-making in agricultural 4.0 contexts. The platform is prepared to integrate new sensor devices, perform data operations, integrate several data sources, transfer complex statistical model developments seamlessly, and provide a user-friendly graphical interface. The proposed software architecture is implemented with open-source technologies and validated in a smart farming scenario. The growth of a batch of pigs at the fattening stage is estimated from the data provided by a level sensor installed in the silo that stores the feed from which the animals are fed. With this application, we demonstrate how farmers can monitor the weight distribution and receive alarms when high deviations happen.

摘要

随着物联网 (IoT) 技术在农业领域的日益普及，智能设备变得越来越普遍。新的、及时的和精确的数据可用性为开发先进的分析模型提供了巨大的机会。因此，用于向最终用户提供新开发的平台是采用物联网技术的关键推动者。这项工作提出了一个基于云的软件平台的通用设计，并使用微服务来实现，以方便在不同的物联网场景下使用预测或规范分析。结合了多种技术来满足平台必须考虑的基本功能——可扩展性、可移植性、互操作性和可用性，以协助农业 4.0 背景下的决策。该平台已准备好集成新的传感器设备、执行数据操作、集成多个数据源、无缝传输复杂的统计模型开发，并提供用户友好的图形界面。所提出的软件架构是使用开源技术实现的，并在智能农业场景中进行了验证。通过安装在储存饲料的筒仓中的液位传感器提供的数据，估计育肥阶段的一批猪的生长情况。通过这个应用，我们演示了农民如何监测重量分布并在出现高偏差时收到警报。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/fdf6eed4225f/sensors-21-05949-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/3b317e11172f/sensors-21-05949-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/6fdbcff17828/sensors-21-05949-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/8f8674001067/sensors-21-05949-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/3e9979daf27f/sensors-21-05949-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/348711f0e1a8/sensors-21-05949-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/2476644b901d/sensors-21-05949-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/af0623cacf2f/sensors-21-05949-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/272e5d68ac7e/sensors-21-05949-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/d04bfbc0f671/sensors-21-05949-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/85fc92387282/sensors-21-05949-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/fdf6eed4225f/sensors-21-05949-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/3b317e11172f/sensors-21-05949-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/6fdbcff17828/sensors-21-05949-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/8f8674001067/sensors-21-05949-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/3e9979daf27f/sensors-21-05949-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/348711f0e1a8/sensors-21-05949-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/2476644b901d/sensors-21-05949-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/af0623cacf2f/sensors-21-05949-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/272e5d68ac7e/sensors-21-05949-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/d04bfbc0f671/sensors-21-05949-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/85fc92387282/sensors-21-05949-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0489/8434670/fdf6eed4225f/sensors-21-05949-g011.jpg

相似文献

1
An Internet of Things Platform Based on Microservices and Cloud Paradigms for Livestock.基于微服务和云范式的畜牧业物联网平台。
Sensors (Basel). 2021 Sep 4;21(17):5949. doi: 10.3390/s21175949.
2
LoRa Communications as an Enabler for Internet of Drones towards Large-Scale Livestock Monitoring in Rural Farms.LoRa 通信作为无人机物联网在农村农场大规模牲畜监测中的使能技术。
Sensors (Basel). 2021 Jul 26;21(15):5044. doi: 10.3390/s21155044.
3
IRRISENS: An IoT Platform Based on Microservices Applied in Commercial-Scale Crops Working in a Multi-Cloud Environment.IRRISENS：一个基于微服务的物联网平台，应用于多云计算环境中的商业规模作物。
Sensors (Basel). 2020 Dec 14;20(24):7163. doi: 10.3390/s20247163.
4
SmartHerd management: A microservices-based fog computing-assisted IoT platform towards data-driven smart dairy farming.智能畜群管理：一种基于微服务的雾计算辅助物联网平台，用于数据驱动的智能奶牛养殖。
Softw Pract Exp. 2019 Jul;49(7):1055-1078. doi: 10.1002/spe.2704. Epub 2019 May 16.
5
An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes.基于微服务和无服务器范式的物联网平台，用于智能农业目的。
Sensors (Basel). 2020 Apr 24;20(8):2418. doi: 10.3390/s20082418.
6
LoRa Based IoT Platform for Remote Monitoring of Large-Scale Agriculture Farms in Chile.基于 LoRa 的物联网平台，用于智利大规模农业农场的远程监控。
Sensors (Basel). 2022 Apr 7;22(8):2824. doi: 10.3390/s22082824.
7
Precision Agriculture Design Method Using a Distributed Computing Architecture on Internet of Things Context.基于物联网分布式计算架构的精准农业设计方法。
Sensors (Basel). 2018 May 28;18(6):1731. doi: 10.3390/s18061731.
8
A Cloud Enabled Crop Recommendation Platform for Machine Learning-Driven Precision Farming.基于机器学习的精准农业云作物推荐平台。
Sensors (Basel). 2022 Aug 22;22(16):6299. doi: 10.3390/s22166299.
9
Review: Smart agri-systems for the pig industry.综述：用于养猪业的智能农业系统。
Animal. 2022 Jun;16 Suppl 2:100518. doi: 10.1016/j.animal.2022.100518. Epub 2022 Apr 22.
10
Applying Blockchain Technology and the Internet of Things to Improve the Data Reliability for Livestock Insurance.应用区块链技术和物联网提高畜牧业保险数据可靠性
Sensors (Basel). 2023 Jul 11;23(14):6290. doi: 10.3390/s23146290.

引用本文的文献

1
Relevant Cybersecurity Aspects of IoT Microservices Architectures Deployed over Next-Generation Mobile Networks.物联网微服务架构在下一代移动网络上部署的相关网络安全方面。
Sensors (Basel). 2022 Dec 24;23(1):189. doi: 10.3390/s23010189.

本文引用的文献

1
An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes.基于微服务和无服务器范式的物联网平台，用于智能农业目的。
Sensors (Basel). 2020 Apr 24;20(8):2418. doi: 10.3390/s20082418.
2
LoRaFarM: A LoRaWAN-Based Smart Farming Modular IoT Architecture.LoRaFarM：一种基于 LoRaWAN 的智能农业模块化物联网架构。
Sensors (Basel). 2020 Apr 4;20(7):2028. doi: 10.3390/s20072028.
3
A Survey on Data Quality for Dependable Monitoring in Wireless Sensor Networks.无线传感器网络中可靠监测的数据质量调查
Sensors (Basel). 2017 Sep 2;17(9):2010. doi: 10.3390/s17092010.
4
The use of Gompertz models in growth analyses, and new Gompertz-model approach: An addition to the Unified-Richards family.Gompertz模型在生长分析中的应用以及新的Gompertz模型方法：对统一理查兹族的补充
PLoS One. 2017 Jun 5;12(6):e0178691. doi: 10.1371/journal.pone.0178691. eCollection 2017.
5
Developing Ubiquitous Sensor Network Platform Using Internet of Things: Application in Precision Agriculture.利用物联网开发泛在传感器网络平台：在精准农业中的应用
Sensors (Basel). 2016 Jul 22;16(7):1141. doi: 10.3390/s16071141.
6
A production planning model considering uncertain demand using two-stage stochastic programming in a fresh vegetable supply chain context.一种在新鲜蔬菜供应链背景下使用两阶段随机规划考虑不确定需求的生产计划模型。
Springerplus. 2016 Jun 22;5(1):839. doi: 10.1186/s40064-016-2556-z. eCollection 2016.