## 4 Proposed DanRETwin Solution
### Overall Framework  
Considering the current status of digital twin applications in the building sector as well as the current solutions developed and implemented in the market, it is noted that most of the mentioned initiatives and commercial solutions focus on newly constructed buildings and utilize Building Information Models (BIM) to develop and implement digital twins. Our current project is driven by the fact that existing buildings generally lack BIMs and are not as well-equipped as newly built ones. Therefore, we propose the innovative 'DanRETwin' digital twin solution, which will be the first of its kind, specifically designed for making informed decisions on optimal energy retrofits, retro-commissioning, and data-driven performance optimization of non-residential existing buildings. These kinds of solutions are yet to be developed and made available in the existing building sector, presenting an opportunity to create a Danish tool and platform that can not only support the scaling of Danish energy retrofit processes, but also contribute to European and global retrofit initiatives. This initiative aligns with the Danish digital construction strategy (published in 2019), which aims to foster development and enhance digitalization in the construction industry. In this context, we propose a groundbreaking digital twin solution called 'DanRETwin'. Its purpose is to facilitate informed decision-making for optimal energy retrofits, retro-commissioning, and data-driven performance optimization of non-residential existing buildings. This project marks a pioneering Danish effort to leverage digitalization and data capabilities in order to streamline and expedite energy retrofitting projects and applications. The digital twin integrates real-time data collected from building energy meters and utilizes innovative patented clamp-on IoT sensor technology. These inputs are combined with adaptable and scalable dynamic building energy models, resulting in a robust and flexible solution. The major differences between the current state of the art and trends in the majority of building energy retrofitting projects and the proposed DanRETwin solution for optimized retrofitting and renovation processes are shown in Figure 5. As highlighted in the figure, most of the current retrofit activities and projects are conducted based on a building-by-building approach, employing static and tabulated approaches and tools with very large assumptions and generic inputs. This hinders realizing the optimal capacity and added value of the retrofit process. In addition, retrofits are performed as a reactive approach, with changes implemented when needed based on feedback from users. This non-systematic approach to retrofitting led to large performance gaps between promised savings and actual savings after retrofits. Nevertheless, such approaches are expensive and time- and resource-consuming. To address these issues, a digital and scalable solution is proposed in this research that can be easily adapted to multiple cases and buildings with minimal adjustments. The proposed solution is based on data from different seamlessly and wirelessly connected and integrated low-cost, clamp-on IoT sensors and meters. This technology allows the users to effortlessly monitor power, flow, heating, and cooling by simply attaching sensor units to the exterior of the cables and pipes without the need for sophisticated technical expertise or system disconnection. This is attained through the implementation of advanced mathematical AI models, eliminating the need for costly and intricate hardware. Nevertheless, the data from different IoT devices are organized and used to develop robust and adaptable energy models for various systems and components. These models form a library from which various components can be selected to fit various cases and applications, allowing an effective, flexible, and efficient use of time and personnel.