Digital Twins from Smart Manufacturing to Smart Cities: A Survey
Abstrak
Digital twins are quickly becoming a popular tool in several domains, taking advantage of recent advancements in the Internet of Things, Machine Learning and Big Data, while being used by both the industry sector and the research community. In this paper, we review the current research landscape as regards digital twins in the field of smart cities, while also attempting to draw parallels with the application of digital twins in Industry 4.0. Although digital twins have received considerable attention in the Industrial Internet of Things domain, their utilization in smart cities has not been as popular thus far. We discuss here the open challenges in the field and argue that digital twins in smart cities should be treated differently and be considered as cyber-physical “systems of systems”, due to the vastly different system size, complexity and requirements, when compared to other recent applications of digital twins. We also argue that researchers should utilize established tools and methods of the smart city community, such as co-creation, to better handle the specificities of this domain in practice.
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Philippe Michiels C. Tampère Athanasios Dalianis + 4 lainnya
1 Mei 2022
Digital twins have generated a lot of hype recently, but questions remain about what the technology actually means and how one can be built for smart cities. There is a lack of unified models and frameworks for data fusions that link the physical and virtual data exchange. This can undermine the uptake of digital twin technology by cities that are unable to tackle urban problems with advanced data-driven solutions. The T-Cell framework developed by the DUET project acts as a container for models, data, and simulations that interact dynamically in a common environment and provide useful insights for smart city decision makers. Dynamic correspondence that links the architecture with models and data makes it possible to monitor and synchronize the state and behavior of the digital twin with the physical environment being mirrored. Individual models are integrated through APIs to form a cloud of models that can be called upon to perform various what-if analyses related to traffic, air quality, or noise pollution. The framework is currently being tested with citizens in three locations in Europe, but it is easily replicable so that any city, no matter its size, vcan leverage the power of digital twins to achieve its policy goals.
K. Siakas G. Lampropoulos
25 Juli 2022
Due to the fierce competitive global market, enterprises need to face and overcome new challenges and requirements to stay ahead of competition. Cyber‐physical systems, Internet of things, and digital twins are some of the contemporary technologies that are used in the context of Industry 4.0 in order to instill intelligence into the industrial sector by changing traditional manufacturing to smart manufacturing. The digitalized and interconnected nature of Industry 4.0 creates new security, privacy, and safety challenges that need to be addressed in order for it to be fully realized. This study presents an overview regarding the use of digital twins as a means to reinforce and secure cyber‐physical systems and Industry 4.0, in general. Digital twins connect the physical and virtual worlds and can be used in combination with other technologies to provide several merits in various sectors, such as real‐time monitoring and controlling, prompt access to dynamic data, constant visualization and analysis, process optimization, advanced decision‐making, and prediction systems. All in all, based on the literature review, digital twins can constitute an essential tool for the realization, reinforcement, and security of cyber‐physical systems and Industry 4.0.
Hansong Xu Jun Wu Xinping Guan + 2 lainnya
2023
Digital twin for the industrial Internet of Things (DT-IIoT) creates a high-fidelity, fine-grained, low-cost digital replica of the cyber-physical integrated Internet for industry. Powered by artificial intelligence (AI) and security technologies, DT-IIoT provides advanced features such as real-time monitoring, predictive maintenance, remote diagnostics, and rapid response for smart IIoT systems. A systematic review of key enabling technologies such as digital twin, AI, and blockchain is essential to develop DT-IIoT and reveal pitfalls. This paper reviews the preliminaries, real-world applications, architectures and models of digital twin-driven IIoT. In addition, advanced technologies for intelligent and secure DT-IIoT are investigated, including state-of-the-art AI solutions such as transfer learning and federated learning, as well as blockchain-based security solutions. Moreover, software tools for high-fidelity digital twin modeling are proposed. A case study on reinforcement learning-based integrated-control, communication, and computing (3C) design is developed to demonstrate the AI-driven intelligent DT-IIoT. Finally, this paper outlines the prospective applications, challenges, and integrations with ABCDE (i.e., AI, Blockchain, cloud computing, big data, edge computing) as the future directions.
C. Guimarães Milan Groshev Jorge Martín-Pérez + 1 lainnya
1 Agustus 2021
Industry 4.0 aims to support smarter and autonomous processes while improving agility, cost efficiency, and user experience. To fulfill its promises, properly processing the data of the industrial processes and infrastructures is required. Artificial intelligence (AI) appears as a strong candidate to handle all generated data, and to help in the automation and smartification process. This article overviews the digital twin as a true embodiment of a cyber-physical system (CPS) in Industry 4.0, showing the mission of AI in this concept. It presents the key enabling technologies of the digital twin such as edge, fog, and 5G, where the physical processes are integrated with the computing and network domains. The role of AI in each technology domain is identified by analyzing a set of AI agents at the application and infrastructure levels. Finally, movement prediction is selected and experimentally validated using real data generated by a digital twin for robotic arms with results showcasing its potential.
Jaskaran Singh M. Azamfar Jay Lee + 1 lainnya
26 Februari 2020
Digital twin (DT) is gaining popularity due to its significant impacts on bridging the gap between the physical and cyber worlds. As reported by Grand View Research, Inc., the global market of DT is expected to reach $26.07 billion by 2025 with a Compound Annual Growth Rate of 38.2%. The growing adoption of cyber-physical system (CPS), Internet of Things, big data analytics, and cloud computing in manufacturing sector has paved the way for low cost and systematic implementation of DT, with promising impacts on (a) product design and development, (b) machine and equipment health monitoring, and (c) product support and services. Successful implementation of DT would increase transparency, cooperation, flexibility, resilience, production speed, scalability, and manufacturing efficiency. Realisation of smart manufacturing requires collaborative and autonomous interactions between sensing, networking, and computational resources across manufacturing assets where data is gathered from physical systems is utilised for the extraction of actionable insights and provision of predictive services. In this study, a reference architecture based on deep learning, DT, and 5C-CPS is proposed to facilitate the transformation towards smart manufacturing and Industry 4.0.
Daftar Referensi
2 referensiUrban Digital Twins for Smart Cities and Citizens: The Case Study of Herrenberg, Germany
Fabian Dembski Michael Ruddat + 3 lainnya
16 Maret 2020
Cities are complex systems connected to economic, ecological, and demographic conditions and change. They are also characterized by diverging perceptions and interests of citizens and stakeholders. Thus, in the arena of urban planning, we are in need of approaches that are able to cope not only with urban complexity but also allow for participatory and collaborative processes to empower citizens. This to create democratic cities. Connected to the field of smart cities and citizens, we present in this paper, the prototype of an urban digital twin for the 30,000-people town of Herrenberg in Germany. Urban digital twins are sophisticated data models allowing for collaborative processes. The herein presented prototype comprises (1) a 3D model of the built environment, (2) a street network model using the theory and method of space syntax, (3) an urban mobility simulation, (4) a wind flow simulation, and (5) a number of empirical quantitative and qualitative data using volunteered geographic information (VGI). In addition, the urban digital twin was implemented in a visualization platform for virtual reality and was presented to the general public during diverse public participatory processes, as well as in the framework of the “Morgenstadt Werkstatt” (Tomorrow’s Cities Workshop). The results of a survey indicated that this method and technology could significantly aid in participatory and collaborative processes. Further understanding of how urban digital twins support urban planners, urban designers, and the general public as a collaboration and communication tool and for decision support allows us to be more intentional when creating smart cities and sustainable cities with the help of digital twins. We conclude the paper with a discussion of the presented results and further research directions.
The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities
S. Bakiras Dhirendra Shukla + 3 lainnya
2021
Digital twinning is one of the top ten technology trends in the last couple of years, due to its high applicability in the industrial sector. The integration of big data analytics and artificial intelligence/machine learning (AI-ML) techniques with digital twinning, further enriches its significance and research potential with new opportunities and unique challenges. To date, a number of scientific models have been designed and implemented related to this evolving topic. However, there is no systematic review of digital twinning, particularly focusing on the role of AI-ML and big data, to guide the academia and industry towards future developments. Therefore, this article emphasizes the role of big data and AI-ML in the creation of digital twins (DTs) or DT-based systems for various industrial applications, by highlighting the current state-of-the-art deployments. We performed a systematic review on top of multidisciplinary electronic bibliographic databases, in addition to existing patents in the field. Also, we identified development-tools that can facilitate various levels of the digital twinning. Further, we designed a big data driven and AI-enriched reference architecture that leads developers to a complete DT-enabled system. Finally, we highlighted the research potential of AI-ML for digital twinning by unveiling challenges and current opportunities.
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