In the quest to achieve net-zero emissions by 2050, the construction and energy sectors are turning to innovative technologies to optimize building performance. A recent study published in ‘The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences’ (translated as ‘The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences’) offers a compelling approach that could revolutionize how we design and retrofit buildings for energy efficiency.
The research, led by Dr. O. Roman from the Department of Information Engineering and Computer Science (IECS) at the University of Trento, Italy, introduces a data-driven pipeline that integrates 3D surveying, computational fluid dynamics (CFD), and digital twin (DT) technologies. This method aims to enhance the analysis of indoor heat distribution, ultimately optimizing sensor placement within indoor spaces.
The study, conducted as part of the Horizon Europe InCUBE project, focuses on a real-world use-case at the Centro Servizi Culturali Santa Chiara in Trento, Italy. By simulating different indoor environmental conditions and technological systems within a digital twin before any physical interventions, the researchers can optimize energy efficiency. This approach supports the proper installation of heating and cooling devices and facilitates the deployment of advanced technologies, including smart HVAC systems, energy-efficient lighting, and automated energy management solutions.
One of the most significant advantages of this method is its ability to prevent the oversizing of technological systems, which is a common issue in traditional building design. “By accurately modeling demand profiles and optimizing sensor placement based on the geometries of digital twins, we can ensure precise system design and improve performance,” explains Dr. Roman. This not only enhances energy efficiency but also minimizes energy waste, leading to substantial cost savings for building owners and operators.
The use of Artificial Intelligence (AI) in these simulations allows for the precise sizing of HVAC systems, including heat pumps and related devices. This level of detail ensures that the systems are tailored to the specific needs of the building, further enhancing their efficiency and effectiveness.
The commercial impacts of this research are profound. For the energy sector, this approach offers a way to design and retrofit buildings that are not only more energy-efficient but also more cost-effective. By optimizing sensor placement and preventing oversizing, building owners can reduce their energy bills and carbon footprint, aligning with global sustainability goals.
Moreover, this method can be applied to a wide range of buildings, from residential homes to commercial structures, making it a versatile tool for the construction and energy industries. As Dr. Roman notes, “This approach can be scaled and adapted to various building types and sizes, making it a valuable asset for any project aiming to improve energy efficiency.”
The integration of 3D surveying, CFD, and digital twin technologies represents a significant advancement in the field of building design and retrofit. By providing a comprehensive and accurate analysis of indoor heat distribution, this method enables engineers and architects to make informed decisions that enhance energy efficiency and reduce waste.
As the world continues to grapple with the challenges of climate change, innovative solutions like this one will be crucial in achieving net-zero emissions. The research led by Dr. Roman and his team at the University of Trento offers a promising path forward, one that could shape the future of building design and energy efficiency.