Occupant-Building Interaction (OBI) model for university buildings

Abstract

Buildings are becoming ever smarter through being equipped with emerging technologies including variety of sensors. With the advances in building automation, the data that can be captured and shared between the building and its occupants has increased in amount and become more complex. However, the effective use of sensors to capture building-generated data and occupant-generated data and the subsequent use of this data to increase the efficacy of interactions between building and their occupants remains a challenge. This research aims at identifying the important data types that are essential to enable efficient two-way communication between buildings and their occupants. Among these, we focus on occupancy data as one of the major types of data that measures the position and movement of occupants inside the building. We also propose a conceptual hybrid framework to collect and use occupancy-data for university buildings and visualize it on a Building Information Modelling (BIM)-based model in real-time. The importance of indoor real-time location sensing (RTLS) in Occupant-Building Interaction (OBI) is highlighted. Proposed conceptual framework will be used to identify occupant location by analysing both coordinate data and contextual data. RFID tags will be used to collect coordinate data and sound sensors will be used to collect contextual data to identify location and support the RTLS system. The analysed occupancy-data can be communicated to the Building Management System (BMS) to help in monitoring occupant movement. It can assist the occupants in navigating inside the building through a dedicated smartphone application (APP).