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From Building Information Model to Digital Twin: A Framework for Building Thermal Comfort Monitoring, Visualizing, and Assessment

Author(s):


ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 8, v. 13
Page(s): 1971
DOI: 10.3390/buildings13081971
Abstract:

The existing building stock is globally responsible for 17.5% of greenhouse gas emissions due to their operation to achieve occupant satisfaction, thus requiring a vast intervention. However, reducing building stock emissions and optimizing building energy performance cannot be considered independently by the users’ well-being. The thermal comfort conditions and their monitoring represent a central issue that could optimize building energy usage while achieving good indoor environmental conditions. This document describes the first findings of ongoing research focused on the development of a building monitoring system, based on the integration of Building Information Modeling tools and sensor technology through Dynamo Visual Programming. Starting from the development of an Asset Information Model, which represents the virtual replica of a building that currently hosts the administrative offices of the municipality of Cagliari, the first step presented in this contribution shows a thermal comfort monitoring system, scalable and modular, that allows effective gathering and elaboration of data about comfort levels in each of the building’s rooms. The system proves to be a helpful support for facility managers to control building thermal comfort conditions and HVAC systems to assure their best operative status or plan suitable interventions to achieve it.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10737041
  • Published on:
    02/09/2023
  • Last updated on:
    14/09/2023
 
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