## 3 Results
### Sound Level Monitoring of the Living Rooms  
Using the data from the sensor nodes, statistical tests were performed to investigate potential differences in the A-weighted equivalent sound levels (dB) and loudness levels (some), with respect to three main factors, namely: (1) the day of the week; (2) the 15-min time slot of the monitoring period; and (3) the living room factor itself. Three analyses were run separately. Since data failed to meet the normality assumption, an alternative non-parametric test was opted for: the Kruskal-Wallis statistics test. To address the research question (a), the first two tests were performed. A first Kruskal-Wallis H test was performed to determine if there were differences in L\({}_{\text{Aeq-15 min}}\) scores between the four days: the \"Monday\", \"Tuesday\", \"Wednesday\", and \"Thursday\" groups. Distributions of L\({}_{\text{Aeq-15 min}}\) scores were not similar for all groups, as assessed by visual inspection of a boxplot reported in Figure 5. The mean rank of L\({}_{\text{Aeq-15 min}}\) scores was not statistically significantly different between groups, \(\chi^{2}(3)=3.478\), \(p=0.324\). Likewise, another Kruskal-Wallis H test was performed to determine if there were differences in Loudness-15 min scores. Distributions of Loudness-15 min scores were not similar for all groups, as assessed by visual inspection of a boxplot reported in Figure 6. The mean rank of L\({}_{\text{Aeq-15 min}}\) scores was not statistically significantly different between groups, \(\chi^{2}(3)=2.583\), \(p=0.460\)  
Figure 4: Overall presence in the living rooms during the observation day. The lack of statistically significant differences between different days of the week was not surprising since during preliminary meetings between the research group and the management teams of the nursing homes it had been reported that activities in the living rooms tend to follow always the same schedule, to provide residents with regular daily patterns. This is, thus, also reflected in the occurring sound sources. A non-systematic visual inspection of the spectrograms of the sound sources is shown in Figure 5.  
Figure 5: Distributions of L\({}_{\text{Aeq-15 min}}\) scores as a function of the day of the week. Figure 6: Distributions of Loudness-15 min scores as a function of the day of the week. level recordings, compared with some field notes collected on site, confirmed this general circumstance. For instance, Figure 7 represents the five-minute interval between 12:00 and 12:05 p.m. in the living room VH1 during the four full days of noise monitoring (Monday to Thursday). It can be noted that some sound sources are repeated over the week, emerging from a similar background noise. Subsequently, in order to address the research question (b), a Kruskal-Wallis H test was performed to determine if there were differences in \(\mathrm{L_{Aeq-15 min}}\) scores between the nine living rooms: the \"VH1\", \"VH2\", \"SJ\", \"LH1\", \"LH2\", \"SV1\", \"SV2\", \"SP1\", and \"SP2\" groups. Distributions of \(\mathrm{L_{Aeq-15 min}}\) scores were not similar for all groups, as assessed by visual inspection of a boxplot reported in Figure 8. The mean ranks of \(\mathrm{L_{Aeq-15 min}}\) scores were statistically significantly different between groups,  
Figure 7: Example of time-frequency spectrograms of the sound levels in VH1: (**a**) Monday; (**b**) Tuesday; (**c**) Wednesday; (**d**) Thursday. Yellow circles identify examples of sounds of cutley and kitchenware while lunch was being served to residents by staff members. White circles identify a cleaning machine; black circles identify a vocalizing, agitated resident during lunch. \(\chi^{2}(8)=224.711\), \(p<0.001\). Likewise, the distributions for the Loudness-15 min scores were not similar for all groups, as assessed by visual inspection of a boxplot reported in Figure 9. The mean ranks of Loudness-15 min scores were statistically significantly different between groups, \(\chi^{2}(8)=309.929\), \(p<0.001\).