Digital twin concepts for linking live sensor data with real-time models

Author:

Jedermann ReinerORCID,Singh Kunal,Lang Walter,Mahajan Pramod

Abstract

Abstract. For taking most advantage of live or real-time sensor measurements, data have to be processed by a single or even by a chain of models on the fly, in contrast to earlier offline simulation solutions. This requirement can be best met by concepts developed under the general term “digital twin” (DT). The step from the Internet of Things (IoT) to a full exploitation of DT solutions entails new challenges but also provides new features, which we discuss based on our example DT solution for remote monitoring of fruit during ocean transportation. A crucial challenge is the transformation of models into an updateable format, necessary to keep the physical object and its modelled representation in sync. A basic new feature of DTs is new software solutions for easy and flexible linking of different models through a streaming platform by implementing an event-driven architecture. We demonstrate a solution for controlling model execution during multiple life cycle phases of the fruit as physical object. An evaluation of response times showed that server performance is sufficient to handle more than 100 DT instances per second.

Funder

Bundesministerium für Bildung und Forschung

Publisher

Copernicus GmbH

Subject

Electrical and Electronic Engineering,Instrumentation

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Novel Energy-Saving Strategies in Apple Storage: A Review;Sustainability;2024-01-25

2. Digital Twin Models: Functions, Challenges, and Industry Applications;IEEE Journal of Radio Frequency Identification;2024

3. A Slim Digital Twin for a Smart City and Its Residents;Proceedings of the 12th International Symposium on Information and Communication Technology;2023-12-07

4. Digital Twin and IoT for Smart City Monitoring;Learning Techniques for the Internet of Things;2023-11-25

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3