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Abstract

Individuals may value a historical building for various reasons other than usefulness or personal attachment, such as its unique architecture or its role as a communal focal point. Since its first apparition in 2009, the field of HBIM (Historic Building Information Modelling) has received a growing interest as a new parametric objects library based on historic architectural data and a mapping system for plotting the library items onto laser scan survey data. However, based on a bibliometric analysis of metadata conducted during this study, the majority of current research on the field focus on the representation of what exists and overlook HBIM as a tool for conservation and prevention.

As the amount of data generated is increasing, and the types of data are getting increasingly complicated, the rapid digital development brings a tremendous amount of new possibilities and tools that can act as a decision making support for heritage buildings. Many researchers argue that the integration of Big Data within BIM is inevitable and that much of its potential is yet to come. This research aims to investigate the integration of IoT (Internet of Things) and open meteorological data onto an HBIM model to report and analyse facade elements and act as a decision making support. Following an extensive analysis of metadata, a framework is proposed. The framework aims to establish the fundamentals of how Big Data analytics can be used as a decision-making tool for a heritage building. By utilising open meteorological data, sensors and Big Data analytics, a digital twin platform is created. It acts as a health monitor for heritage building's facades, where the results can be expressed in three levels of development based on the level of detail required.

Course: Building Information Management - MSc - P2657FTC

Date Deposited: 2022-03-28

URI/permalink: https://library.port.ac.uk/dissert/dis13866.html