# An open-BIM Approach to IoT Integration with Incomplete As-Built Data
## 4 Case Study  
The proposed methodology has been applied to the Institute for Manufacturing (IfM) building located in the West Cambridge campus of the University of Cambridge. It is part of the West  
Figure 2: Research schema. Cambridge DT Research Facility [18] and has been equipped with a customised IoT sensor network, comprising a set of Monnit ([[https://www.monnit.com/Products/Sensor/](https://www.monnit.com/Products/Sensor/)]([https://www.monnit.com/Products/Sensor/](https://www.monnit.com/Products/Sensor/))) wireless sensors measuring indoor environmental and asset parameters, for instance, temperature (\({}^{\circ}\)C), relative humidity (\(\%\)), CO\({}_{2}\) concentration (ppm) of indoor spaces and window open/close status, and HVAC pump vibration frequency (Hz) among others. A BMS, based on the Trend ([[http://www.trendcontrols.com/en-GB/](http://www.trendcontrols.com/en-GB/)]([http://www.trendcontrols.com/en-GB/](http://www.trendcontrols.com/en-GB/))) platform, is currently used to monitor the performances of mechanical, electrical and pumping (MEP) systems. This data remains in a different system and is not integrated with the IoT sensor data. Thus, it cannot easily be used together to make informed decisions on assets operations. To demonstrate the capability of the designed scheme, a typical anomaly detection application for the HVAC system monitoring is implemented [35]. Assets responsible for delivering the functionalities of the building determine the quality of the services and the comfort of the spaces that it provides for its inhabitants. Monitoring the working condition of the assets and further revealing the raised anomalies, either environmental or asset-wise, is important for guaranteeing building operational performance. As a result of the limitation in computational resources for buildings, the performances of HVAC system components are monitored individually without considering their interdependence. Even for individual component, the monitoring of assets anomaly detection, for operation and maintenance management requires comprehensive data sources, both static and dynamic, for re-classifying building facilities information. For the definition of the static information requirements, the following information has been considered:  
* Geometries and location of the HVAC components, including primary air loop, variable refrigerant flow (VRF), water circulation pumps and radiators;
* Relevant data in the civil components of the building (technical specifications, active contracts, maintenance records, models and producer of the components);
* Sensor location and technical specifications;
* System architecture, that is, the way the HVAC system is organised from multiple components, according to a classification system;
* Interface requirements with the real-time platform. The real-time information requirements are defined considering the following:  
* Set points for the HVAC system (e.g., the temperature of the rooms, relative humidity, CO\({}_{2}\) concentration);
* Data on comfort parameters measurements (BMS, Monnit sensors);
* Data on the BMS and IoT sensors status. Table 2 collects the information requirements defined for two rooms (labelled G.44 and 1.58) and the related assets in the building. According to the anomaly detection application needs, the level of aggregation of the assets has been defined. This new bespoke classification has been employed to group the relevant building elements to be monitored through the anomaly detection application. Some were already present in the initial version of the IFC file (i.e., Table 2 marked as Existing \"yes\"), while others had to be created (as non-geometrical classes). In the modelling procedure, the IFC2x3 TC1 [53] version has been used. This version, despite being improved by Version 4, offers wider software support, allowing more accurate visualisation of complex geometries, especially in commercial software. However, the possibility to upgrade the workflow with more recent IFC versions has been considered.