Factors Influencing Adoption of Digital Twin Advanced Technologies for Smart City Development: Evidence from Malaysia

Buildings, Год журнала: 2023, Номер 13(3), С. 775 - 775

Опубликована: Март 15, 2023

Digital Twin Technology (DTT) has gained significant attention as a vital technology for the efficient management of smart cities. However, its successful implementation in developing countries is often hindered by several barriers. Despite limited research available on city development Malaysia, there need to investigate possible challenges that could affect effective DTT country. This study employs mixed methodology design, comprising an interview, pilot survey, and main survey. Firstly, we identified barriers reported literature excluded insignificant factors through interviews. Next, conducted Exploratory Factor Analysis (EFA) survey results further refine factors. Finally, performed Structural Equation Modeling (SEM) analysis data develop model identifies Malaysia. Our findings suggest presence 13 highly barriers, which are divided into four formative constructs. We found personalization crucial, while operational were less important

Язык: Английский

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Next-generation energy systems for sustainable smart cities: Roles of transfer learning

Sustainable Cities and Society, Год журнала: 2022, Номер 85, С. 104059 - 104059

Опубликована: Июль 19, 2022

Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while improving grid stability and meeting service demand. This is possible adopting next-generation systems, which leverage artificial intelligence, the Internet of things (IoT), communication technologies collect analyze big data in real-time effectively run city services. However, training machine learning algorithms perform various energy-related tasks sustainable smart a challenging science task. These might not as expected, take much time training, or do have enough input generalize well. To that end, transfer (TL) has been proposed promising solution alleviate these issues. best authors' knowledge, this paper presents first review applicability TL for systems well-defined taxonomy existing frameworks. Next, an in-depth analysis carried out identify pros cons current techniques discuss unsolved Moving on, two case studies illustrating use (i) prediction with mobility (ii) load forecasting sports facilities are presented. Lastly, ends discussion future directions.

Язык: Английский

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Digital Twins for Healthcare 4.0—Recent Advances, Architecture, and Open Challenges

IEEE Consumer Electronics Magazine, Год журнала: 2022, Номер 12(6), С. 29 - 37

Опубликована: Сен. 23, 2022

Recent trends have shown a widespread increase in the landscape of digital healthcare (i.e., Healthcare 4.0) services, such as personalized healthcare, intelligent rehabilitation, telemedicine, and smart diet management, among others. These services are based on variety diverse requirements. Fulfilling these requirements require proactive analytics self-sustainability networks. Self-sustainability enables operation network with minimum possible interaction from end-users/network operators, whereas efficient management resources response to users’ requests. To enable 4.0 online self-sustainability, one can leverage twins. In this article, we present an overview recent advances twins for 4.0. An architecture is also proposed. Furthermore, several use cases Finally, open research challenges solutions.

Язык: Английский

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Digital twin-supported smart city: Status, challenges and future research directions

Expert Systems with Applications, Год журнала: 2023, Номер 217, С. 119531 - 119531

Опубликована: Янв. 9, 2023

Язык: Английский

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A Comprehensive Survey on Federated Learning Techniques for Healthcare Informatics

Computational Intelligence and Neuroscience, Год журнала: 2023, Номер 2023(1)

Опубликована: Янв. 1, 2023

Healthcare is predominantly regarded as a crucial consideration in promoting the general physical and mental health well‐being of people around world. The amount data generated by healthcare systems enormous, making it challenging to manage. Many machine learning (ML) approaches were implemented develop dependable robust solutions handle data. ML cannot fully utilize due privacy concerns. This primarily happens case medical Due lack precise clinical data, application for same may not yield desired results. Federated (FL), which recent development where computation offloaded source appears be promising solution this problem. In study, we present detailed survey applications FL informatics. We initiate discussion on need domain, followed review papers. focus fundamentals major motivations behind applications. then along with state art several verticals healthcare. Then, lessons learned, open issues, challenges that are yet solved also highlighted. future directions give prospective researchers willing do their research domain.

Язык: Английский

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Big data, machine learning, and digital twin assisted additive manufacturing: A review

Materials & Design, Год журнала: 2024, Номер 244, С. 113086 - 113086

Опубликована: Июнь 25, 2024

Additive manufacturing (AM) has undergone significant development over the past decades, resulting in vast amounts of data that carry valuable information. Numerous research studies have been conducted to extract insights from AM and utilize it for optimizing various aspects such as process, supply chain, real-time monitoring. Data integration into proposed digital twin frameworks application machine learning techniques is expected play pivotal roles advancing future. In this paper, we provide an overview twin-assisted AM. On one hand, discuss domain highlight machine-learning methods utilized field, including material analysis, design optimization, process parameter defect detection monitoring, sustainability. other examine status current technical approach offer future developments perspectives area. This review paper aims present convergence big data, learning, Although there are numerous papers on additive others twins AM, no existing considered how these concepts intrinsically connected interrelated. Our first integrate three propose a cohesive framework they can work together improve efficiency, accuracy, sustainability processes. By exploring latest advancements applications within domains, our objective emphasize potential advantages possibilities associated with technologies

Язык: Английский

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Metaverse Communications, Networking, Security, and Applications: Research Issues, State-of-the-Art, and Future Directions

IEEE Communications Surveys & Tutorials, Год журнала: 2023, Номер 26(2), С. 1238 - 1278

Опубликована: Дек. 25, 2023

Metaverse is an evolving orchestrator of the next-generation Internet architecture that produces immersive and self-adapting virtual world in which humans perform activities similar to those real world, such as playing sports, doing work, socializing. It becoming a reality driven by ever-evolving advanced technologies extended reality, artificial intelligence, blockchain. In this context, will play essential role developing smart cities, becomes more evident post-COVID-19-pandemic metropolitan setting. However, new paradigm imposes challenges, novel privacy security threats can emerge digital ecosystem. Moreover, it requires convergence several media types with capability quickly process massive amounts data keep residents safe well-informed, raise issues related scalability interoperability. light this, research study aims review literature on state art integrating concepts cities. First, paper presents theoretical discusses international companies' interest emerging technology. also examines notion relevant identifies prevalent threats, determines importance communication infrastructure information gathering for efficient operation. Next, blockchain discussed regarding preservation how provide tamper-proof content sharing among users. Finally, application distributed social good highlighted. Most importantly, explores reflections cutting-edge technology city, talks about impact production urban policies, eventually gaps future directions domain.

Язык: Английский

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Use of Metaverse Technology in Education Domain

Journal of Metaverse, Год журнала: 2023, Номер 3(1), С. 79 - 86

Опубликована: Фев. 21, 2023

Metaverse is the digital mirror of physical world where users are connected as individual avatars. The purpose virtual surface it should gather and actual-time global statistics also inquire for immersion to link worlds. Users’ inputs may be used train artificial intelligence (AI) systems provide client with highly customized offerings. This technology offers an appropriate answer in sphere education training by using its process. By extended reality, sector will changed drastically. study outlined required principles approaches transforming utilizing Metaverse. Qualitative method has been analyzing. In addition, ten key techniques based on Metaverse’s quality standards have outlined. research impact whole visualizing contents, campus, 3D simulation, remote which accessible all including underdeveloped countries. Additionally, anticipated developments industry highlighted. Finally, a model classroom proposed Mozilla Hubs platform, can group discussion, seminar, thesis meeting, presentation many more bring changes system eventually. main our improve engaging students from developing under-developing countries, well providing facilities education.

Язык: Английский

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Explainable AI for cybersecurity automation, intelligence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects

ICT Express, Год журнала: 2024, Номер 10(4), С. 935 - 958

Опубликована: Май 21, 2024

Digital twins (DTs) are an emerging digitalization technology with a huge impact on today's innovations in both industry and research. DTs can significantly enhance our society quality of life through the virtualization real-world physical system, providing greater insights about their operations assets, as well enhancing resilience real-time monitoring proactive maintenance. also pose significant security risks, intellectual property is encoded more accessible, continued synchronization to counterparts. The rapid proliferation dynamism cyber threats digital environments motivate development automated intelligent solutions. Today's industrial transformation relies heavily artificial intelligence (AI), including machine learning (ML) data-driven technologies that allow machines perform tasks such self-monitoring, investigation, diagnosis, future prediction, decision-making intelligently. However, effectively employ AI-based models context cybersecurity, human-understandable explanations, trustworthiness, factors when making decisions scenarios. This article provides extensive study explainable AI (XAI) based cybersecurity modeling taxonomy XAI methods assist analysts professionals comprehending system functions, identifying potential anomalies, ultimately addressing them DT manner. We discuss how these play key role solving contemporary issues various applications. conclude this paper by crucial challenges avenues for further research, directions researchers might approach model future-generation field.

Язык: Английский

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Data Security and Privacy in the Age of AI and Digital Twins

Advances in business information systems and analytics book series, Год журнала: 2024, Номер unknown, С. 99 - 124

Опубликована: Янв. 4, 2024

Data security and privacy have emerged as businesses struggle with the growing digitization of operations abundance data in age artificial intelligence digital twins. An overview issues solutions relating to context AI twins is given this chapter. The chapter emphasizes value classification recognizing how sensitive being created used is. necessity strong measures, such access controls, authentication procedures, encryption methods, emphasized order safeguard against unwanted breaches. To further assure compliance, underlines significance ongoing monitoring, auditing, risk assessment procedures. It examines successfully detect mitigate problems by utilizing real-time routine audits, proactive assessments.

Язык: Английский

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