## 4 Results and Discussion  
Figure 2 shows the results obtained from the indoor Rn concentration between 18 September 2020 and 16 March 2022. This sequence, which evaluated 546 consecutive days, shows an average value for the indoor Rn concentration of 485.8 \(\pm\) 237.4 Bq\(\cdot\)m\({}^{-3}\), contributing to a scenario of potential high-risk exposure for the occupants who occupy the room daily. The evolution of the concentration over time also shows high variability in the measured data, with values oscillating between a minimum of 43.7 Bq\(\cdot\)m\({}^{-3}\) and a maximum of 1446.7 Bq\(\cdot\)m\({}^{-3}\). Figure 1: RnProbe IoT edge building blocks and LoRaWAN operation modes (adapted from [30]). According to Figure 2, the results can be represented using a sinusoid curve, which reflects a periodic, harmonic type of behavior for indoor Rn variation over time, following therefore a repetitive trend, as shown with the orange line superimposed on the black line representing the indoor Rn concentration. The layout of the results seems to point to a cycle that reaches maximum values in the winter and minimum values in the summer, among which it can be highlighted that the highest values occurred on 13 February 2021 and 2 January 2022, and the lowest values on 21 September 2020 and 12 July 2021, respectively, in winter and summer. The values recorded around the minimum value, which occurred between maximum peaks (13 February 2021 and 2 January 2022), seem to correspond to a transition zone between cycles, which adjusts to a probable correlation with other parameters, such as temperature, atmospheric pressure, or relative humidity. The temperature recorded inside the compartment with the RnProbe also presents a sinusoidal behavior, as shown in Figure 3, where a very likely negative correlation seems to be more than evident. The determination of Pearson's correlation coefficient between the sets of indoor Rn concentration and temperature results shows a value of \(-0.7\), justifying, as observed in Figure 3, that there is an inversely proportional correlation between temperature and the concentration of Rn. A prior investigation carried out by [PERSON] et al. [55] obtained results that closely align with the findings of this study. The authors discovered that in two settings where the dominant ventilation mechanism was through unintentional air leakage points during the winter, positive correlations between radon concentration and outdoor temperature were observed, with values reaching 0.94 and 0.92, respectively. Conversely, in settings with improved airtightness, negative correlations (R = \(-0.96\) and R = \(-0.62\)) were found between the radon concentration and outdoor temperature. The cause of this correlation between temperature and indoor Rn concentration is still without a causal explanation, and to justify this finding, it needs to be further studied and related to other parameters, such as atmospheric pressure and relative humidity. As [PERSON] [56] found, the processes involved in the transport of Rn by atmospheric aerosols strongly influence the fluxes and concentration of indoor Rn and depend on  
Figure 2: Evolution of the indoor Rn concentration over the period under review. The black line represents the indoor Rn concentration, and the orange line represents the oscillation over time, determined using the recorded peaks (maximum and minimum) and the respective occurrence dates. the physical properties of the free atoms and the activity size distributions of the atmospheric aerosol. Despite this apparent correlation between temperature and indoor Rn concentration, it is necessary to analyze this finding with some care since the RnProbe probe was placed in a compartment on the ground floor of the building, where several computer racks with servers are located. Therefore, the temperature suffers a significant increase, which should be around 5 to 15 \({}^{\circ}\)C, compared to the average compartment temperature throughout the year, thus influencing the calculation of relative humidity.