Cognitive Twins for Supporting Decision-Makings of Internet of Things Systems

Autor:	Lu, Jinzhi, Zheng, Xiaochen, Gharaei, Ali, Kalaboukas, Kostas, Kiritsis, Dimitris
Rok vydání:	2019
Předmět:	Electrical Engineering and Systems Science - Systems and Control
Zdroj:	AMP 2020
Druh dokumentu:	Working Paper
Popis:	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 stakeholders 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. Comment: 11pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1912.08547 Zobrazit plný text záznamu View this record from Arxiv