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.
翻译:传统建模(BIM)系统的设计并不是要处理由建设中的互联网(IoT)传感器所释放的大量高速数据,因为历史没有考虑到这些数据的实时性质,这意味着这类BIM系统的产出通常缺乏颁布决定所必需的及时性,因为感官数据出现模式,同样,随着传感器越来越多地部署在建筑物中,陈旧的建筑管理系统(BMS)难以保持功能,因为互操作性的挑战不断增加,这些因素加在一起促使需要填补智能建筑研究方面的一个重要空白,以便通过将BIM、BMS和传感器数据结合起来,更快地采用这些技术。本文描述了适应性城市平台的数据结构,目的是通过在时间和空间进行综合BIM和实时传感器数据分析,满足这些综合要求。