Digital twins in the building sector: Implementation and key features

The building industry is a major contributor to global CO2 emissions and energy consumption, accounting for 37% of CO2 emissions and 36% of global energy demand in 2020. Traditional construction practices and reliance on fossil fuels exacerbate the environmental impact of this sector. Despite advancements in building technology, energy use and emissions continue to rise, necessitating innovative solutions to enhance sustainability. Digital Twin (DT) technology offers a promising approach by creating virtual replicas of physical buildings, enabling real-time monitoring, simulation, and optimization of building performance. By integrating sensor data and Building Information Models (BIM), DTs provide comprehensive insights into energy usage, fault detection, predictive maintenance, and operational efficiency. This paper explores the implementation methodologies, key features, and applications of DTs in the building sector, highlighting their potential to significantly reduce energy consumption and greenhouse gas emissions. Additionally, the study addresses the benefits of advanced technologies such as big data, cloud computing, artificial intelligence (AI), and the Internet of Things (IoT) in enhancing BIM capabilities and supporting data-driven decision-making. The findings demonstrate that DTs can transform asset management practices, improve building performance, and promote sustainability in the building industry.