# An Automated IoT Visualization BIM Platform for Decision Support in Facilities Management
## 1 Introduction
While the BIM modeling technology encompasses building information and visualization, it lacks the means to incorporate information concerning the immediate environment into the model, and must be aided by a plug-in (e.g., Revit API, Firefly) if it is to achieve a further step towards intelligent building. [PERSON] (2014) confirmed the effectiveness of the scripting language Dynamo as a parametric design tool in a case study, and successfully used data from Arduino environmental sensors (humidity, sunlight and CO\({}_{2}\)) in a BIM model, while changing 3D model parameters [16]. [PERSON] et al. (2017) established two prototypes for the purpose of preliminary research. Prototype 1 used the software tools Revit (Autodesk BIM authoring tool) and Dynamo (visual programming environment for Revit) for modeling, while Prototype 2 used the software tools Rhino (3D modeling environment) and Grasshopper (visual programming environment). This research effort proposed considering physical interaction, in addition to computer programming, as an alternative method of establishing parametric models, which presents architects with significant difficulties. The prototypes demonstrated a new approach for determining the type of object relationships, generating parametric equations, and application in the context of design [17]. [PERSON] et al. (2015) suggested that simulation analysis data can serve as important design criteria when designers are designing a building, and proposed and employed a BIM-based performance optimization (BPOpt) framework; this framework used Dynamo to collect sensor data from buildings, and can optimize buildings' energy performance and spatial daylighting based on simulated environmental data [18]. Table 1 shows the comparison of the proposed platform with the results of three studies [16; 17; 18]. Several researchers have attempted to integrate sensor information with BIM information such as visualizations ([19]) and building management systems ([20,21]). [PERSON] et al. (2018) [19] found that the data obtained from a building's structural health diagnosis could not be effectively and systematically integrated with other relevant monitoring data to support asset management, and proposed a dynamic parametric BIM approach making use of time-series sensor data to support data-driven and dynamic visualization. This approach involves the dynamic visualization of key structural performance parameters, and achieves real-time updating, long-term management of data, and model transformation via the IFC format, while also serving to increase the value of data. [PERSON] (2017) [20] developed a framework using three-dimensional spatial characteristics and sensor location data, and incorporated building management system (BMS) sensor data to make it easier for users and managers to perform facility management; a case study was employed to explore the use of data from various sensors during the operating phase. [PERSON] (2015) [21] developed a web-based graphical user interface (GUI) integrating BIM with BMS data in order to help managers and users perform visual browsing of spatial data, and to make building performance information more readily accessible to all building stakeholders, which can both boost energy management awareness and also support decision-making during the operating stage. Since the aforementioned studies explore BIM applications targeting a single building and its occupants or stakeholders, their methods cannot be applied directly to a school campus, which usually involves multiple buildings with different ages, and multiple occupant/stakeholder groups, structures, equipment, and facility management protocols. Most existing cases in the literature successfully solved target facility management problems through the use of numerical computations using data from sensors monitoring building spaces. However, failure to integrate the data with a BIM model of the building will hinder the facility manager's ability to identify potential problems intuitively.