在亚洲的收割机上使用通用工作流进行远程信息处理的优化架构适配

Lukas Viebrock, C. Netramai
{"title":"在亚洲的收割机上使用通用工作流进行远程信息处理的优化架构适配","authors":"Lukas Viebrock, C. Netramai","doi":"10.1109/RI2C56397.2022.9910282","DOIUrl":null,"url":null,"abstract":"Global challenges in agriculture demand continuous innovation, nowadays mostly driven by digital farming solutions. Connected agricultural machines with telematics are already a common appearance in developed markets such as Europe and North America. However, Asia offers still largely untapped potential in the agricultural sector. Enabling telematics for complex agricultural machines such as combine harvesters offers considerable benefits but also comes with a multitude of interconnected components and interdisciplinary technologies. Unknown challenges make it difficult to assess the cost, development effort and process planning for the expansion which creates a significant market entry barrier for industrial companies. This paper provides a holistic view of technical challenges categorized into effects from the different application environment, the suitability of the connectivity hardware and the legal boundaries related to the architectural system design. Finally, all necessary analysis steps and interconnections are visualized in a generic workflow to significantly improve the decision making process.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"175 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimized Architectural Adaption using a Generic Workflow for Telematics on Harvesters in Asia\",\"authors\":\"Lukas Viebrock, C. Netramai\",\"doi\":\"10.1109/RI2C56397.2022.9910282\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Global challenges in agriculture demand continuous innovation, nowadays mostly driven by digital farming solutions. Connected agricultural machines with telematics are already a common appearance in developed markets such as Europe and North America. However, Asia offers still largely untapped potential in the agricultural sector. Enabling telematics for complex agricultural machines such as combine harvesters offers considerable benefits but also comes with a multitude of interconnected components and interdisciplinary technologies. Unknown challenges make it difficult to assess the cost, development effort and process planning for the expansion which creates a significant market entry barrier for industrial companies. This paper provides a holistic view of technical challenges categorized into effects from the different application environment, the suitability of the connectivity hardware and the legal boundaries related to the architectural system design. Finally, all necessary analysis steps and interconnections are visualized in a generic workflow to significantly improve the decision making process.\",\"PeriodicalId\":403083,\"journal\":{\"name\":\"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)\",\"volume\":\"175 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RI2C56397.2022.9910282\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RI2C56397.2022.9910282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

全球农业挑战需要持续创新,目前主要由数字农业解决方案驱动。在欧洲和北美等发达市场,带有远程信息处理功能的联网农业机械已经很常见。然而,亚洲在农业领域仍有很大未开发的潜力。为复杂的农业机械(如联合收割机)提供远程信息处理提供了相当大的好处,但也伴随着大量相互连接的组件和跨学科技术。未知的挑战使得评估成本、开发努力和流程规划变得困难,这对工业公司造成了重大的市场进入障碍。本文提供了技术挑战的整体视图,这些技术挑战分为不同应用程序环境的影响、连接硬件的适用性以及与体系结构系统设计相关的法律边界。最后,所有必要的分析步骤和相互联系在通用工作流中可视化,以显着改善决策过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Optimized Architectural Adaption using a Generic Workflow for Telematics on Harvesters in Asia
Global challenges in agriculture demand continuous innovation, nowadays mostly driven by digital farming solutions. Connected agricultural machines with telematics are already a common appearance in developed markets such as Europe and North America. However, Asia offers still largely untapped potential in the agricultural sector. Enabling telematics for complex agricultural machines such as combine harvesters offers considerable benefits but also comes with a multitude of interconnected components and interdisciplinary technologies. Unknown challenges make it difficult to assess the cost, development effort and process planning for the expansion which creates a significant market entry barrier for industrial companies. This paper provides a holistic view of technical challenges categorized into effects from the different application environment, the suitability of the connectivity hardware and the legal boundaries related to the architectural system design. Finally, all necessary analysis steps and interconnections are visualized in a generic workflow to significantly improve the decision making process.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Hyperparameter Tuning in Convolutional Neural Network for Face Touching Activity Recognition using Accelerometer Data RI2C 2022 Cover Page CNN based Automatic Detection of Defective Photovoltaic Modules using Aerial Imagery Metaverse for Developing Engineering Competency A Comparative Study of Deep Convolutional Neural Networks for Car Image Classification
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1