![]() Kabadayi S, Pridgen A, Julien C (2006) Virtual sensors: abstracting data from physical sensors. Van der Aalst WMP et al (2018) Views on the past, present, and future of business and information systems engineering. Value based and intelligent asset management. Negri E, Fumagalli L, Macchi M (2020) A review of the roles of digital twin in CPS-based production systems. Love PED, Matthews J (2019) The ‘how’ of benefits management for digital technology: from engineering to asset management. In: Proceedings of the international conference on offshore mechanics and arctic engineering-OMAE, vol 1. Tygesen UT, Jepsen MS, Vestermark J, Dollerup N, Pedersen A (2018) The true digital twin concept for fatigue re-assessment of marine structures. įarrar CR, Lieven NAJ (2007) Damage prognosis: the future of structural health monitoring. įlah M, Nunez I, Chaabene WB, Nehdi ML (2021) Machine learning algorithms in civil structural health monitoring: a systematic review. įarrar CR, Worden K (2007) An introduction to structural health monitoring. ![]() Giurgiutiu V (2014) Structural health monitoring with piezoelectric wafer active sensors, 2nd edn. It is concluded from the study that the decision-making using VT could contribute to the development of a digital BIM model which can assist in leading professional SHM practices. A laboratory model has been used to characterize and evaluate the framework, which indicated that there was a damage pattern present. The real-time data monitoring from IoT sensors was visualized using programmable nodes created in Revit Dynamo. The digital BIM model of a portal frame was programmed to respond to the physical sensors. The digital BIM model of a structure is created to customize the parametric and develop a virtual model to visualize the structural behaviour over time. Using BIM and digital twin frameworks, this study aims to design a framework for developing a virtual twin (VT) framework to automate the process of real-time data monitoring and virtual visualization of the structure. The decision-making process for structural failure detection requires the visualization of large amounts of data in real time. ![]() A growing number of data recording sensors are being used to analyse the distress patterns of structural elements in the global construction industry. ![]() Construction monitoring is an important phase since it involves basic aspects of repair and maintenance of buildings. BIM (building information modelling) enhances the management of large construction projects and infrastructure projects. ![]()
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