# IoT Open-Source Architecture for the Maintenance of Building Facilities
## 4 Case Study  
This section explains the case study setup, the allocation of sensors, the algorithms to monitor and detect anomalies in building facilities, and summarize the achieved results.  
The case study has been operated at the Politecnico di Torino in the DISEG Laboratory. The laboratory room is located below ground in the department. Figure 7 shows the case study building: (a) geolocation and (b) BIM model Revit software representation. In all the rooms, fan coils are located under the windows.  
Figure 6: BIM–IoT data integration and visualization approach diagram.  
The case study fan-coil motor is made by EMI (EuroMotors Italia), type FC83M-2014/1 with a 4 possible speeds. The FC motor rotates in an anti-clockwise direction at 1100 revolutions per minute (RPM) at maximum speed. Moreover, FC has a cooling or heating battery and a filter that must often be monitored; to provide an automatic preventive maintenance system, the FC is equipped with sensors to acquire real-time data.  
More technical details of the FC are provided in Table 3.  
The ESP8266 sensor node is placed on the FC together with sensors. All the collected data from the room facilities are sent to the BIM using the Forge API; Autodesk Forge API provides the client ID and client password to access the uploaded customized BIM on the cloud; using the callback URL everyone can access the IoT-integrated BIM dashboard. A general schematic diagram of sensors' locations of the FCs, sensor boards, and data acquisition system of the BIM model is showed in Figure 8.  
The system is powered with simple USB cables and starts collecting data from the installed sensor nodes in the room. The Rpi3B mainboard then connects to the ESP8266 and RPIZCT4V3T2 sensor nodes and starts acquiring data from sensors and at the same time registers these data to the MySQL database. Using the developed extensions on the Visual Studio Code for Autodesk Forge Viewer, collected IoT data and the 3D building model of Revit can be visualized together on the Forge Viewer through a static URL and port provided by Forge API. The functional flowchart of the whole system is shown in Figure 9.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model** & **V/HZ** & **Ampere** & **Num Speeds** & **Power** & **RPM** \\
**Number** & & & & & \\ \hline FC & & & & & \\
83M-2014/1 & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Technical specifications of FC Motor FC 83M-2014/1.  
Figure 7: Case study building: (**a**) geolocation on the maps.google.it and (**b**) 2D view of the case study room with the location of the FC.  
Figure 8: Sensors’ location in the FC and building facilities.  
Figure 9: Functional flowchart of the system.  
FC with wireless sensor nodes (b), FC battery with installed temperature sensors (a), the motor with a temperature sensor (c), and room sensors with the sensor node (d) are shown in Figure 10.  
Data are measured by fan coil and room sensors and then displayed on the dashboard of the Rpi3B server using Node-Red flows in Figure 11.  
Measured and integrated variables with their descriptions on the Node-Red flow besides the dashboard are provided in Table 4.  
To verify the IoT and BIM integrated application dashboard, one voltage (V1) and one current (I1) sensors are connected to the first port of the sensor's board and all temperature sensors including RTD are allocated to the FC as shown in Figure 8.  
Figure 11: Node-Red flows of the FC and room sensors data acquisition system.  
Figure 10: Case study sensor nodes placement to the room and FC: (**a**) FC battery and temperature sensor, (**b**) FC with RPIZCT4V3T2 board, (**c**) motor with temperature sensor, and (**d**) room equipped with ESP826 sensor node.