## 4 Results and Discussion
In any case, despite being positively impacted by the presence of computer equipment in the room, it can be assumed that the temperature follows a pattern equivalent to the natural one, although with the addition of the cumulative effect of the presence of the artificial thermal source. As demonstrated in the work presented by [PERSON] et al. [57], the air change rate, indoor temperature, and moisture significantly affected the indoor Rn concentration, with the authors confirming the tendency for the indoor Rn concentration to be minimal for higher temperatures. Because of this situation, the questions must be asked whether temperature can be used as a mitigation measure and whether indoor Rn concentration can be controlled, not only by renewing the air (ventilation) but also by ensuring that this air is within a specific range of temperature and of relative humidity. For example, [PERSON] et al. suggest ranges for temperature and relative humidity of 20-22 \({}^{\circ}\)C and 50-60%, respectively. However, further and deeper analyses are required to be able to validate this possibility. Still, it seems that right now, justifying the use of active probes for the continuous monitoring of indoor environments, with the capacity to simultaneously record multiparameter information, such as temperature, atmospheric pressure, and relative humidity, requires the ability to analyze the parallel evolution of the different parameters and to establish correlations (or not) between them. The lowest value for the indoor Rn concentration recorded during the monitoring period was 43.7 Bq\(\cdot\)m\({}^{-3}\) on 21.09.2020. Suppose one analyzes the daily positive increments based on this reference value for the indoor Rn concentration that occurred in the periods (Figure 3) in which there is a rise or fall in that concentration. In that case, the results shown  
Figure 3: Superimposition showing the evolution of the temperature recorded in the compartment under analysis in this study (black line) and the sinusoidal representative for the evolution of the indoor Rn concentration (orange line) during the period in which the monitoring took place. in Table 1 are obtained. As can be seen in the results obtained, the occurrences of an increase in the indoor Rn concentration are mostly associated with periods in which the temperature drops, also confirming in these periods that the rate of growth in the concentration of the indoor Rn is higher. In this case, the expected relationship between the indoor temperature and relative humidity does not show a correlation, with a Pearson coefficient practically equal to zero. This apparent disconnection between temperature and relative humidity must be associated with the influence that artificial thermal sources have on the behavior of temperature, so this parameter does not, in this situation under study, contribute to the understanding of the processes that lead to the evolution of the concentration of the indoor Rn in a particular trend. The relative humidity registered with the RnProbe in the period under analysis presented an average value of 32.6 \(\pm\) 5.4% and a variation between 17.0% and 44.2%. This observation is because relative humidity is a measure dependent on the temperature of the air, so the higher the air temperature, the greater its ability to absorb moisture. In this way, evaluating the impact that the relative humidity may have on the evolution of the indoor Rn concentration in this specific situation is not possible.