A BIM-Based Approach for Decision Support System in Smart Buildings

Abstract

Building information model (BIM) is primarily a 3D digital representation of a structure and features such as geometry, spatial relationships, and geographic information to support integrated design. BIM in recent years has evolved from simple 3D to interacting with virtual and augmented reality. Such interaction aims to improve work productivity, home comfort, and entertainment, common Internet of things (IoT) goals. The IoT represents a possible evolution of the use of the Internet in which objects are able to communicate data about themselves and with other devices autonomously. One of the main goals of IoT is to build a digital copy of the real world. Therefore, BIM and IoT can integrate through data acquired in a BIM model; this model can be helpful in predictive analysis as needed. This paper aims to describe a methodology that allows the visualization and representation of data from sensors within the BIM environment to support decisions, sometimes complex, requiring interdisciplinary expertise. The study focusses on a real case study: a scale prototype of a single-family house that includes several sensors capable of producing data that feed a database based on the predictive/decision-making phase developed through machine learning techniques. The proposed methodology integrates an IoT-based platform that allows communication between sensors and Dynamo software to access sensor data, automatically updating the information contained in the BIM model.