| 1. |
- Yitmen, Ibrahim, et al.
(författare)
-
Integration of Digital Twins, Blockchain and AI in Metaverse Enabling Technologies and Challenges
- 2023
-
Ingår i: Cognitive Digital Twins for Smart Lifecycle Management of Built Environment and Infrastructure. - : CRC Press. - 9781003230199 ; , s. 39-64
-
Bokkapitel (refereegranskat)abstract
- The Metaverse is the post-reality universe, a perpetual and persistent multiuser environment merging physical reality with digital virtuality. It is based on the convergence of technologies that enable multisensory interactions with virtual environments, digital objects, and people, such as virtual reality (VR), augmented reality (AR), and mixed reality (MR). Due to the "Internet of Everything's" paradigm shift from big data to decentralized small data, blockchain technology will be critical in achieving the metaverse at mobile edge networks. On the other hand, combining Artificial Intelligence (AI) and blockchain with the metaverse poses significant research hurdles as of the characteristics of digital commodities and marketplaces, transaction volumes in metaverse systems are substantially greater compared to the physical world. This chapter discusses the integration of Digital Twin (DT), Blockchain, and AI into the Metaverse, emphasizing enabling technologies and difficulties. It enables seamless embodied user communication in real-time and dynamic interactions with digital artifacts.
|
|
| 2. |
- Yitmen, Ibrahim, et al.
(författare)
-
Knowledge Graph-based Approach for Adopting Cognitive Digital Twins in Shop-floor of Modular Production
- 2023
-
Ingår i: Cognitive Digital Twins for Smart Lifecycle Management of Built Environment and Infrastructure Challenges, Opportunities and Practices. - : CRC Press. - 9781003230199 ; , s. 79-100
-
Bokkapitel (refereegranskat)abstract
- Digital Twins (DT) is an emerging technology that helps activities in process simulation, monitoring, and control as well as develops insights on process parameter relationships to achieve high quality AEC activities. As an evolution, CDTs make use of technologies and services designed to give DTs cognitive skills similar to those of humans. On the other hand, the knowledge graph powered by cognition may be used to multi-source heterogeneous data of customized items to achieve autonomous data fusion. This chapter provides the framework for the cognitive modular production paradigm by detailing a data representation technique based on a knowledge graph that can be utilized to enable reasoning and decision-making via graph embedding. The data from the Industrial Internet of Things (IIoT) is combined using an internal knowledge tree with many layers. The cognitive module receives the device's process knowledge and analyzes it for the whole line in order to predict the device's perception and cognition actions. These reactions are made feasible through the use of perception and cognitive systems. This chapter presents an IIoTs-enabled knowledge graph-based data representation approach for cognitive modular production and focuses on how to construct a shop-floor CDT and implementation process using Model-based Systems Engineering (MBSE).
|
|
