Data Management for Building Information Modelling in a Real-Time Adaptive City Platform

Abstract

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. CCS CONCEPTS• Computer systems organization → Real-time system architecture; • Information systems → Information integration.

From building to city level dynamic digital Twin: a review from data management perspective

“…There were also studies proposing DT architectures for both building and city levels, which have been included in the following section of this paper. Besides, based on the summarised data sources, creating a shared data environment with BIM and IoT was the most addressed issue [5,13,15,17]. And since the traditional building management systems indicated in Table 1 provided thorough building facility data, the integration of these data with BIM and IoT tends to be a necessity.…”

“…And since the traditional building management systems indicated in Table 1 provided thorough building facility data, the integration of these data with BIM and IoT tends to be a necessity. Furthermore, a dominant trend of the summarised DT studies is that the shared data environments have been designed as web-based platforms or systems [13,15,16,18]. They intended to solve the webbased data integration problems like data sources mapping, interpretation etc.…”

“…For example, RFID or QR code bridge the gap between existing building facilities and their virtual counterparts. Multiple building systems like BMS and BAS in the operation and maintenance (O&M) phase collect data through sophisticated sensors and devices [12] and the systems usually deal with low-volume low-velocity data [13]. In addition, data from IoT devices collect real-time data from the built environment with features of highvolume, high-velocity.…”