An Integrated BIM-IoT approach to support energy monitoring

BIM, Building Information Model, is considered the 3D representation of an artifact and its characteristics such as geometry, spatial relationships, and geographical information to support integrated design. With recent developments in BIM, there has been a shift from simple 3D to interact with virtual and augmented reality. This innovation drives improvements in work productivity, home comfort, and entertainment, common goals of the Internet of Things (IoT). Therefore, 3D and sensors can integrate through data captured in a BIM model, an environment that lends itself well to the visualization of the results of Machine Learning operations. This paper proposes a methodology that allows data visualization and representation from sensors within a BIM model to support design decisions that fall under different disciplines. The research focuses on a real case study of a university classroom that includes several sensors capable of recording data that feed a database based on the predictive/decisional phase developed through Machine Learning techniques to optimize electrical consumption. The proposed methodology integrates an IoT cloud platform that allows the optimal management and monitoring of electricity consumption in a public environment through a model updated in real-time.