Mohit Taneja, Nikita Jalodia, John Byabazaire, Alan Davy, Cristian Olariu
{"title":"SmartHerd管理：一个基于微服务的雾计算辅助物联网平台，面向数据驱动的智能奶牛养殖。","authors":"Mohit Taneja, Nikita Jalodia, John Byabazaire, Alan Davy, Cristian Olariu","doi":"10.1002/spe.2704","DOIUrl":null,"url":null,"abstract":"<p><p>Internet of Things (IoT), fog computing, cloud computing, and data-driven techniques together offer a great opportunity for verticals such as dairy industry to increase productivity by getting actionable insights to improve farming practices, thereby increasing efficiency and yield. In this paper, we present SmartHerd, a fog computing-assisted end-to-end IoT platform for animal behavior analysis and health monitoring in a dairy farming scenario. The platform follows a microservices-oriented design to assist the distributed computing paradigm and addresses the major issue of constrained Internet connectivity in remote farm locations. We present the implementation of the designed software system in a 6-month mature real-world deployment, wherein the data from wearables on cows is sent to a fog-based platform for data classification and analysis, which includes decision-making capabilities and provides actionable insights to farmer towards the welfare of animals. With fog-based computational assistance in the SmartHerd setup, we see an 84% reduction in amount of data transferred to the cloud as compared with the conventional cloud-based approach.</p>","PeriodicalId":49504,"journal":{"name":"Software-Practice & Experience","volume":"49 7","pages":"1055-1078"},"PeriodicalIF":2.6000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/spe.2704","citationCount":"51","resultStr":"{\"title\":\"SmartHerd management: A microservices-based fog computing-assisted IoT platform towards data-driven smart dairy farming.\",\"authors\":\"Mohit Taneja, Nikita Jalodia, John Byabazaire, Alan Davy, Cristian Olariu\",\"doi\":\"10.1002/spe.2704\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Internet of Things (IoT), fog computing, cloud computing, and data-driven techniques together offer a great opportunity for verticals such as dairy industry to increase productivity by getting actionable insights to improve farming practices, thereby increasing efficiency and yield. In this paper, we present SmartHerd, a fog computing-assisted end-to-end IoT platform for animal behavior analysis and health monitoring in a dairy farming scenario. The platform follows a microservices-oriented design to assist the distributed computing paradigm and addresses the major issue of constrained Internet connectivity in remote farm locations. We present the implementation of the designed software system in a 6-month mature real-world deployment, wherein the data from wearables on cows is sent to a fog-based platform for data classification and analysis, which includes decision-making capabilities and provides actionable insights to farmer towards the welfare of animals. With fog-based computational assistance in the SmartHerd setup, we see an 84% reduction in amount of data transferred to the cloud as compared with the conventional cloud-based approach.</p>\",\"PeriodicalId\":49504,\"journal\":{\"name\":\"Software-Practice & Experience\",\"volume\":\"49 7\",\"pages\":\"1055-1078\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/spe.2704\",\"citationCount\":\"51\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software-Practice & Experience\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1002/spe.2704\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2019/5/16 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software-Practice & Experience","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1002/spe.2704","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2019/5/16 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
SmartHerd management: A microservices-based fog computing-assisted IoT platform towards data-driven smart dairy farming.
Internet of Things (IoT), fog computing, cloud computing, and data-driven techniques together offer a great opportunity for verticals such as dairy industry to increase productivity by getting actionable insights to improve farming practices, thereby increasing efficiency and yield. In this paper, we present SmartHerd, a fog computing-assisted end-to-end IoT platform for animal behavior analysis and health monitoring in a dairy farming scenario. The platform follows a microservices-oriented design to assist the distributed computing paradigm and addresses the major issue of constrained Internet connectivity in remote farm locations. We present the implementation of the designed software system in a 6-month mature real-world deployment, wherein the data from wearables on cows is sent to a fog-based platform for data classification and analysis, which includes decision-making capabilities and provides actionable insights to farmer towards the welfare of animals. With fog-based computational assistance in the SmartHerd setup, we see an 84% reduction in amount of data transferred to the cloud as compared with the conventional cloud-based approach.
期刊介绍：
Software: Practice and Experience is an internationally respected and rigorously refereed vehicle for the dissemination and discussion of practical experience with new and established software for both systems and applications.
Articles published in the journal must be directly relevant to the design and implementation of software at all levels, from a useful programming technique all the way up to a large scale software system. As the journal’s name suggests, the focus is on practice and experience with software itself. The journal cannot and does not attempt to cover all aspects of software engineering.
The key criterion for publication of a paper is that it makes a contribution from which other persons engaged in software design and implementation might benefit. Originality is also important. Exceptions can be made, however, for cases where apparently well-known techniques do not appear in the readily available literature.
Contributions regularly:
Provide detailed accounts of completed software-system projects which can serve as ‘how-to-do-it’ models for future work in the same field;
Present short reports on programming techniques that can be used in a wide variety of areas;
Document new techniques and tools that aid in solving software construction problems;
Explain methods/techniques that cope with the special demands of large-scale software projects. However, software process and management of software projects are topics deemed to be outside the journal’s scope.
The emphasis is always on practical experience; articles with theoretical or mathematical content are included only in cases where an understanding of the theory will lead to better practical systems.
If it is unclear whether a manuscript is appropriate for publication in this journal, the list of referenced publications will usually provide a strong indication. When there are no references to Software: Practice and Experience papers (or to papers in a journal with a similar scope such as JSS), it is quite likely that the manuscript is not suited for this journal. Additionally, one of the journal’s editors can be contacted for advice on the suitability of a particular topic.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
