# Methods for Noise Event Detection and Assessment of the Sonic Environment by the Harmonic Index
## 3 Results and Discussion  
Figure 6 reports the box plots of the acoustic parameters L\({}_{\text{Aeq}}\), the noise climate L\({}_{\text{A10}}\)-L\({}_{\text{A90}}\), the intermittency ratio (IR), and the event component (EVT) of the Harmonic index for all 92-time series, together with the estimated normal distribution curve on the left side of each box plot. The variability is fairly large and covers a reasonable range of environmental noise time patterns, usually occurring in urban areas. The available data did not include the spectrum and the overall unweighted dB level and, therefore, the analysis was limited to dB(A) data. However, these types of data are, very often, the output of the noise monitoring networks usually installed in urban areas, mainly to check the compliance of the environmental noise with the limits issued by the legislation. Since, at least at the Milan sites, it was not possible to check whether the noise events detected by the four algorithms matched with their real occurrences during the monitoring time, the analysis was aimed to compare the considered detection algorithms. The number of events detected by each of the four algorithms is reported in the box plots of Figure 7, for every site and day of monitoring. Figure 5: ANED computation block diagram, with a first filtering stage, a feature extraction algorithm (MFCC) every 30-msec window, and a frame-level classifier, with a final high-level decision based on a majority vote every 1 s.  
two algorithms and those recognized by the algorithms L50 (685, the lowest number of events) and O10 (929). These two algorithms on average detected \(-\)59% of events than those recognized by IR and Lr. The algorithms IR and Lr in their definition differed for the threshold, with the former having a fixed value equal to L\({}_{\rm AeqT}\), referred to the measurement time (T), and the latter an adaptive value equal to the running L\({}_{\rm Aeq,run}\), while for both, the exceedance (E) above the threshold was equal to 3 dB. In particular, IR detected a higher number of events than that obtained for Lr for 42% of the 92-time histories of 1 s A-weighted short L\({}_{\rm Aeq}\), a lower one for 50%, and the same number for 8%. As mentioned above, the algorithms L50 and O10 seem suitable to detect notice-events; the former having a fixed threshold equal to L\({}_{\rm A50}\) + 10 dB and the latter looking at a sum of progressive increases of the A-weighted SPL greater than 10 dB from the SPL at the event start time \(\tau_{\rm e}\) (see Figure 3). We should note that, in Milan, the site with high traffic flow (MhT) showed a number of events lower than those observed for moderate (MmT) and low (MIT) traffic flow for all algorithms. This was most likely due to the louder background noise produced by the higher number of vehicles passing-by, as confirmed by the intermittency ratio equal to 31.3%, on average, for MhT, compared to 44.3% and 63.4% for MmT and MIT, respectively. Figure 8 reports the box plots of the percentage of the number of events with conditions (C), referred to those without conditions (NC) and detected by the four algorithms, at each site and day of monitoring in compliance with an event duration \(\tau\) longer than 2 s, and a time gap between events \(\tau_{\rm g}\) of 5 (T5) or 10 s (T10). Figure 8: Box plots of the percentage of the number of conditioned events, referred to those “not conditioned”, and detected by the four algorithms, at each site and day of monitoring, in compliance with an event duration \(>\) 2 s and a time gap between events \(\tau_{\rm g}\) of 5 (T5) or 10 s (T10). The considered conditions for the noise events largely reduce the number of detected noise events compared to those without conditions (NC), with the exception of the O10 algorithm. This suggests that most noise fluctuations are not recognized as noise events. Regarding noise exposure, Figure 9 shows the box plots of SEL values for not conditioned (NC) events versus conditioned events detected by the four algorithms.