@inproceedings{c7fc090d1c124a29b680404d0955a76b,
title = "Cognitive twins for supporting decision-makings of internet of things systems",
abstract = "Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for identifying the dynamics of virtual model evolution, promoting the understanding of interrelationships between virtual models and enhancing the decision-making based on DT. The CT ensures that assets of Internet of Things (IoT) systems are well-managed and concerns beyond technical stake holders are addressed during IoT system development. In this paper, a Knowledge Graph (KG) centric framework is proposed to develop CT. Based on the framework, a future tool-chain is proposed to develop the CT for the initiatives of H2020 project FACTLOG. Based on the comparison between DT and CT, we infer the CT is a more comprehensive approach to support IoT-based systems development than DT.",
keywords = "Cognitive Twins, Decision-making, Internet of Things, Knowledge Graph",
author = "Jinzhi Lu and Xiaochen Zheng and Ali Gharaei and Kostas Kalaboukas and Dimitris Kiritsis",
note = "Publisher Copyright: {\textcopyright} The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.; 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing, AMP 2020 ; Conference date: 01-06-2020 Through 04-06-2020",
year = "2020",
doi = "10.1007/978-3-030-46212-3\_7",
language = "英语",
isbn = "9783030462116",
series = "Lecture Notes in Mechanical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "105--115",
editor = "Lihui Wang and Majstorovic, \{Vidosav D.\} and Dimitris Mourtzis and Emanuele Carpanzano and Govanni Moroni and Galantucci, \{Luigi Maria\}",
booktitle = "Proceedings of 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing, AMP 2020",
address = "德国",
}