开发支持人工智能的工业物联网平台——从早期用例验证中吸取的经验教训

Holger Eichelberger, Gregory Palmer, Svenja Reimer, Tat Trong Vu, H. Do, Sofiane Laridi, Alexander Weber, Claudia Nieder'ee, Thomas Hildebrandt
{"title":"开发支持人工智能的工业物联网平台——从早期用例验证中吸取的经验教训","authors":"Holger Eichelberger, Gregory Palmer, Svenja Reimer, Tat Trong Vu, H. Do, Sofiane Laridi, Alexander Weber, Claudia Nieder'ee, Thomas Hildebrandt","doi":"10.48550/arXiv.2207.04515","DOIUrl":null,"url":null,"abstract":"For a broader adoption of AI in industrial production, adequate infrastructure capabilities are crucial. This includes easing the integration of AI with industrial devices, support for distributed deployment, monitoring, and consistent system configuration. Existing IIoT platforms still lack required capabilities to flexibly integrate reusable AI services and relevant standards such as Asset Administration Shells or OPC UA in an open, ecosystem-based manner. This is exactly what our next level Intelligent Industrial Production Ecosphere (IIP-Ecosphere) platform addresses, employing a highly configurable low-code based approach. In this paper, we introduce the design of this platform and discuss an early evaluation in terms of a demonstrator for AI-enabled visual quality inspection. This is complemented by insights and lessons learned during this early evaluation activity.","PeriodicalId":386831,"journal":{"name":"European Conference on Software Architecture","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Developing an AI-enabled IIoT platform - Lessons learned from early use case validation\",\"authors\":\"Holger Eichelberger, Gregory Palmer, Svenja Reimer, Tat Trong Vu, H. Do, Sofiane Laridi, Alexander Weber, Claudia Nieder'ee, Thomas Hildebrandt\",\"doi\":\"10.48550/arXiv.2207.04515\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For a broader adoption of AI in industrial production, adequate infrastructure capabilities are crucial. This includes easing the integration of AI with industrial devices, support for distributed deployment, monitoring, and consistent system configuration. Existing IIoT platforms still lack required capabilities to flexibly integrate reusable AI services and relevant standards such as Asset Administration Shells or OPC UA in an open, ecosystem-based manner. This is exactly what our next level Intelligent Industrial Production Ecosphere (IIP-Ecosphere) platform addresses, employing a highly configurable low-code based approach. In this paper, we introduce the design of this platform and discuss an early evaluation in terms of a demonstrator for AI-enabled visual quality inspection. This is complemented by insights and lessons learned during this early evaluation activity.\",\"PeriodicalId\":386831,\"journal\":{\"name\":\"European Conference on Software Architecture\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Conference on Software Architecture\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.48550/arXiv.2207.04515\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Conference on Software Architecture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48550/arXiv.2207.04515","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

为了在工业生产中更广泛地采用人工智能,充足的基础设施能力至关重要。这包括简化AI与工业设备的集成,支持分布式部署、监控和一致的系统配置。现有的工业物联网平台仍然缺乏以开放的、基于生态系统的方式灵活集成可重用人工智能服务和相关标准(如资产管理shell或OPC UA)所需的能力。这正是我们下一代智能工业生产生态圈(IIP-Ecosphere)平台所要解决的问题,它采用了一种高度可配置的低代码方法。在本文中,我们介绍了该平台的设计,并讨论了人工智能视觉质量检测演示器的早期评估。在早期评价活动中获得的见解和经验教训补充了这一点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing an AI-enabled IIoT platform - Lessons learned from early use case validation
For a broader adoption of AI in industrial production, adequate infrastructure capabilities are crucial. This includes easing the integration of AI with industrial devices, support for distributed deployment, monitoring, and consistent system configuration. Existing IIoT platforms still lack required capabilities to flexibly integrate reusable AI services and relevant standards such as Asset Administration Shells or OPC UA in an open, ecosystem-based manner. This is exactly what our next level Intelligent Industrial Production Ecosphere (IIP-Ecosphere) platform addresses, employing a highly configurable low-code based approach. In this paper, we introduce the design of this platform and discuss an early evaluation in terms of a demonstrator for AI-enabled visual quality inspection. This is complemented by insights and lessons learned during this early evaluation activity.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信