Abstract
Energy Management has gained increasing value in construction market. The spread of Building Information Modelling (BIM) as a methodology for the construction processes organization will bring progressively to a digitalized asset management. Taking a step further, the concept of Digital Twin (DT) is being used to integrate building’s assets with digital technologies to allow real-time analysis, as well as to provide simulation capabilities. DT is expected to have high impact on facilitating sustainable transition through technological developments, according to the European Green Deal mission. Considering operation and maintenance phase in building lifecycle, one of the main problems is about data management. Energy managers and decision-makers use indeed text and spreadsheets to visualize and interpret data. The most recent software solutions in this field focus mostly on the collection of information in a systematic way and in document and deadlines management. This approach helps operators but makes it difficult to understand the real-time building’s performance. Furthermore, the indoor environmental performance in dynamic use conditions is rarely considered in decision processes. Therefore, a more efficient and less error-prone method is needed for the real-time management of heterogeneous data. A new approach which combines BIM and Internet of Things (IoT) technology could create a shared data environment for crossed management energy aspects. Equipping the building with monitoring systems means that a large amount of collectible data needs to be managed. This paper describes an attempt to represent and visualize sensor data in BIM, in a user-friendly way to support complex decisions as a significantly improved alternative compared to the traditional ways.The proposed framework is tested and verified on the case study of a school building within the project “SINCRO”. In the first part of the paper the use case, devices, and the proposed BIM-IoT integration workflow are described. In the second part the resulting cloud-based DT is explained together with its functionalities applied to a testing period. Feedbacks of the energy manager are collected to demonstrate how real-time performance information can lead to more responsive building management and improve energy efficiency.