  Legacy Building Information Modelling (BIM) systems are not designed to
process the high-volume, high-velocity data emitted by in-building
Internet-of-Things (IoT) sensors. Historical lack of consideration for the
real-time nature of such data means that outputs from such BIM systems
typically lack the timeliness necessary for enacting decisions as a result of
patterns emerging in the sensor data. Similarly, as sensors are increasingly
deployed in buildings, antiquated Building Management Systems (BMSs) struggle
to maintain functionality as interoperability challenges increase. In
combination these motivate the need to fill an important gap in smart buildings
research, to enable faster adoption of these technologies, by combining BIM,
BMS and sensor data. This paper describes the data architecture of the Adaptive
City Platform, designed to address these combined requirements by enabling
integrated BIM and real-time sensor data analysis across both time and space.
