## 5 Results and Discussion
### Measurements and Interpretation  
In addition to the results regarding the overall equipment and the process, the data measured so far also already provide interesting insights, some of which are described below. For comparison purposes, different EnOcean-based sensors where installed in the same room. Figure 8 displays values from five temperature sensors over the span of four days. The sensor models used are given in Table 7.  
First of all, it is noticeable that the shape of the curves is quite similar among all sensors. Nevertheless, differences regarding the numerical resolution, time resolution, and reaction time can be observed. When using EnOcean, a longer time resolution is generally to be expected, as the protocol is designed for low power consumption. This becomes particularly visible in combination with larger resolutions (e.g., with sensor A having a resolution of 0.32 K). Figure 8: Comparison of temperature measurements with different EnOcean sensors in the same room. Based on these different sensor measurements, we also investigated the effects of the different measurement options on the temperature control in a first small control experiment. We used different control modes and different sensors serving as the input for a temperature controller that set the valve-opening values in the room. A part of the results is displayed in Figure 9. The time spans were selected to give similar conditions, such as ambient temperature or temperatures at the beginning of the plots. Due to the fact that the experiments were run in a real-world setting, there are still some differences since identical conditions cannot be guaranteed. Nevertheless, the data can be used to reveal interesting insights. The results shown in subplot (Figure 9a) were obtained during the operation where only a temperature set-point was sent to the actuator. The selected Micropelt MVA005 uses a locally measured and processed room temperature and an internal controller. Compared to the other plots, relatively large oscillations become visible. One possible explanation for this is the local proximity of the temperature sensor to the radiator, which makes it difficult to estimate the room air temperature, especially in dynamic heating phases. Even though the control performance is lowered compared to the other subplots, this ability is an \begin{table}
\begin{tabular}{l c c} \hline \hline
**Sensor Index in Figure 8** & **Manufacturer** & **Model Name** \\ \hline A & Eltako & FTFSB \\ \hline B & Nodon & temperature and humidity sensor \\ \hline C & Thermokon & SR06 \\ \hline D & Pressac & 60.CO2 SLR TMP HUM868 \\ \hline E & Nodon & temperature sensor \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Sensor models for the comparison of temperature measurements. Figure 9: Comparison of temperature control with different measurements. (**a**) shows a control mode where no explicit temperature measurement is used but only a desired temperature is sent to the EnOcean valve actuator (Micropelt MVA005). The date of experiment was 4 February 2021. (**b**) shows a time span where a proportional controller in the cloud is used, with measurement input from the Pressac sensor and \(K_{P}=150\). The data was sampled on 2 March 2021. (**c**) shows a time span where a control with \(K_{P}=150\) is also used, but the measurements to feed the controller were those taken from the Nodon sensor. The experiment was conducted on 16 February 2021.  
important backup functionality, as described in Section 3. Subplots (b) and (c) show data within times where a controller in the cloud calculated valve-position set-points, which were sent to the valve actuator. In both times, a proportional controller with \(K_{P}=150\) was used. The difference between the subplots is the temperature measurement used by the controller. In the case of subplot (b), the measurement by the Pressac sensor was used, and in the case of (c), the measurement by the Nodon sensor was used.