Archives of Computational Methods in Engineering, Год журнала: 2023, Номер 31(3), С. 1341 - 1362
Опубликована: Окт. 24, 2023
Язык: Английский
Archives of Computational Methods in Engineering, Год журнала: 2023, Номер 31(3), С. 1341 - 1362
Опубликована: Окт. 24, 2023
Язык: Английский
Engineering Applications of Artificial Intelligence, Год журнала: 2023, Номер 126, С. 106813 - 106813
Опубликована: Июль 25, 2023
Язык: Английский
Процитировано
48Automation in Construction, Год журнала: 2023, Номер 158, С. 105240 - 105240
Опубликована: Дек. 21, 2023
Язык: Английский
Процитировано
47Automation in Construction, Год журнала: 2023, Номер 158, С. 105210 - 105210
Опубликована: Ноя. 30, 2023
Язык: Английский
Процитировано
46International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 43
Опубликована: Фев. 27, 2024
The metaverse has emerged as an exciting new paradigm for human-computer interaction (HCI) and virtual collaboration. This paper presents a comprehensive review of the to address gap in existing literature where there is lack survey that reviews nature its building blocks from human-centric perspective. We first synthesize definition delineate key affordances. then introduce detailed framework encompassing metaverse's nature, infrastructure technologies, input/output technologies facilitate multi-sensory HCI, alongside applications across diverse domains. components within this are explained depth, offering insights into readiness level current technologies. Based on analysis, we outline major open challenges propose promising directions demanding further exploration investigation. By clarifying vision characterizing required realize it, provides essential serves invaluable resource developers researchers working advance transformative medium.
Язык: Английский
Процитировано
35Journal of Environmental Management, Год журнала: 2024, Номер 368, С. 122144 - 122144
Опубликована: Авг. 11, 2024
Язык: Английский
Процитировано
21Buildings, Год журнала: 2023, Номер 13(11), С. 2725 - 2725
Опубликована: Окт. 29, 2023
Effective civil infrastructure management necessitates the utilization of timely data across entire asset lifecycle for condition assessment and predictive maintenance. A notable gap in current maintenance practices is reliance on single-source instead heterogeneous data, decreasing accuracy, reliability, adaptability, further effectiveness engineering decision-making. Data fusion thus demanded to transform low-dimensional decisions from individual sensors into high-dimensional ones decision optimization. In this context, digital twin (DT) technology set revolutionize industry by facilitating real-time processing informed However, data-driven smart using DT not yet achieved, especially terms fusion. This paper aims establish a conceptual framework harnessing with ensure efficiency infrastructures throughout their lifecycle. To achieve objective, systematic review 105 papers was conducted thematically analyze approaches frameworks management, including applications, core technologies, challenges. Several gaps are identified, such as difficulty integration due heterogeneity, seamless interoperability, difficulties associated quality, maintaining semantic features big technological limitations, complexities algorithm selection. Given these challenges, research proposed emphasizing multilayer fusion, open building information modeling (openBIM) geographic system (GIS) immersive visualization stakeholder engagement, adoption extended foundation classes (IFC)
Язык: Английский
Процитировано
35Journal of Infrastructure Intelligence and Resilience, Год журнала: 2023, Номер 2(3), С. 100053 - 100053
Опубликована: Авг. 15, 2023
Structural Health Monitoring (SHM) has become a paramount necessity in civil engineering for improving the operational performance of aging infrastructure. Recent monitoring techniques have utilized emerging technologies Industry 4.0, such as Internet Things, Big Data analytics, cloud computing, and cybersecurity, to automate SHM methodologies. However, they found challenges linking these developing an autonomous, well-established digital framework applications SHM. Visualizing processed data real-time interface generates multiple obstacles, witnessing delays transfer resorting offline tools manual processing. This paper, therefore, explores integration Building Information Modeling (BIM) Things (IoT) through Arduino micro-processing unit tracking visualizing from time frequency domains. Strategies enabling processing are developed while continuously acquiring structural responses. The query is established web-based database instead storing resources that await intervention. proposed methodology validated experimentally using two practical applications: dynamically moving vehicle over simply-supported bridge prototype randomly excited three-story model with visualization both time- frequency-domain information under undamaged damaged conditions. research develops early-phase Digital Twin (DT) present static dynamic rich-fed BIM database.
Язык: Английский
Процитировано
29Advances in Applied Energy, Год журнала: 2023, Номер 12, С. 100155 - 100155
Опубликована: Окт. 6, 2023
The urban energy infrastructure is facing a rising number of challenges due to climate change and rapid urbanization. In particular, the link between morphology systems has become increasingly crucial as cities continue expand more densely populated. Achieving neutrality adds another layer complexity, highlighting need address this relationship develop effective strategies for sustainable infrastructure. occurrence extreme events can also trigger cascading failures in system components, leading long-lasting blackouts. This review paper thoroughly explores incorporating into models through comprehensive literature proposes new framework enhance resilience interconnected systems. emphasizes integrated provide deeper insights design operation addresses failures, interconnectivity, compound impacts urbanization on It emerging opportunities, including requirement high-quality data, utilization big integration advanced technologies like artificial intelligence machine learning proposed integrates classification, mesoscale microscale process consider influence morphology, variability, events. Given prevalence climate-resilient strategies, study underscores significance improving accommodate future variations while recognizing interconnectivity within
Язык: Английский
Процитировано
28Energy and Buildings, Год журнала: 2025, Номер unknown, С. 115392 - 115392
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1IEEE Journal of Radio Frequency Identification, Год журнала: 2024, Номер 8, С. 282 - 321
Опубликована: Янв. 1, 2024
In the rapidly evolving landscape of Industry 4.0, digital twins have emerged as a transformative technology across various industrial sectors. This paper presents comprehensive, in-depth review twin models in terms concept and evolution, fundamental components frameworks, existing based on their functionalities. The also discusses how are used/adopted different industries highlights challenges potential solutions to address current issues. aims provide researchers industry professionals with clear insight into unique benefits applications models. will help comprehend significance for specific purposes foster advancement state-of-the-art techniques this field.
Язык: Английский
Процитировано
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