Abstract
This study proposes a digitalization framework for historic buildings. In this framework, advanced techniques, like Internet of Things (IoT), cloud computing, and artificial intelligence (AI), are utilized to create digital twins for historic buildings. A digital twin is a software representation of a physical object. This study uses digital twins to protect, predict, and optimize through analytics of real-time and historical data of selected features. Heterogeneous data of historic buildings, such as indoor environment, energy consumption metering, and outdoor climate, are collected with proper sensors or retrieved from other data sources. Then, these data are periodically uploaded and stored in the database of the cloud platform. Based on these data, AI models are trained through appropriate machine learning algorithms to monitor historic buildings, predict energy consumption, and control energy-consuming equipment autonomously to reach the balance of energy efficiency, building conservation, and human comfort. The cloud-based characteristic of our digitalization framework makes the digital twins developed in this study easy to be transplanted to many other historic buildings in Sweden and other countries.
Highlights
In the European Union, 35 % of buildings are over 50 years old, and almost 75 % of buildings are energy inefficient [1]
artificial intelligence (AI) models are trained through appropriate machine learning algorithms to monitor historic buildings, predict energy consumption, and control energy-consuming equipment autonomously to reach the balance of energy efficiency, building conservation, and human comfort
The cloud-based characteristic of our digitalization framework makes the digital twins developed in this study easy to be transplanted to many other historic buildings in Sweden and other countries
Summary
In the European Union, 35 % of buildings are over 50 years old, and almost 75 % of buildings are energy inefficient [1]. Improving energy efficiency of historic buildings contributes to reducing energy consumption and lowering greenhouse gas emissions. Many factors can affect the energy consumption of a building. Typical factors include weather conditions outside the building, characteristics of the building itself, and occupancy inside the building [2]. Figuring out how a building currently consumes energy is a critical step in reducing energy consumption. It helps optimize the scheduling of heating, ventilation, and air conditioning (HVAC) systems. It provides a benchmark for the renovation, which can quantify energy efficiency improvements after the renovation [3]
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