# Optimized Sensors Network and Dynamical Maps for Monitoring Traffic Noise in a Large Urban Zone
## 5 Conclusions  
Dynamap is the first automatic monitoring system, based on customized low cost sensors and a software tool implemented on a general purpose GIS platform, performing the update of noise maps in real time (dynamic noise maps) on a large urban area. The update of noise maps is accomplished by scaling pre-calculated basic noise maps. The latter are selected and scaled using the information retrieved from low cost sensors continuously measuring the sound pressure levels of the primary noise sources present in the mapping area. A complete basic noise map covering the entire survey area is calculated and saved for each source. Scaled basic noise maps of each primary source are then energetically summed up to provide the overall noise map of the area. In this way, the need for several and expensive software license is extremely reduced and limited only to the preparation of the basic noise maps. The proposed method of noise mapping is essentially a statistically-based approach, whose predictive power over the entire road network relies on the assignment of a non-acoustic parameter to each road stretch. This is an essential requirement that must be complied to generalize Dynamap project to other cities. The non-acoustic parameter must show a high degree of correlation with the road traffic noise level. In the case of the District 9 (Z9) of the city of Milan, the correlation was about (60-65)%. In terms of accuracy, the predictive capability of the Dynamap scheme is mainly associated with the related accuracy of the chosen non-acoustic parameter. For this reason, a poor accuracy in the latter is directly reflected on the noise prediction error. For example, in the case in which the non-acoustic parameter is provided by a road traffic flow model (here taken as the total daily traffic flow), eventual errors in the traffic noise predictions can be traced back to a discrepancy between the measured and the model predicted hourly traffic flows. As a by-product of Dynamap, the use of the non-acoustic parameter generalizes the standard concept of road categorization, which has been used so far in most applications. The overall mean prediction error of Dynamap for Z9 is estimated to be about 3 dB, which can be seen as a very promising result for most practical applications. Specifically, Dynamap predicts real-time traffic noise at any site within the pilot zone, by relying on the noise measurements of 24 monitoring stations properly located within the zone. For practical purposes, the whole set of roads has been divided into six groups, within which the constituting roads display similar traffic noise dynamics. Therefore, the process generates six dynamic acoustic maps. The predicted noise level at a generic location is given by a combination of the six dynamically updated maps. The error associated with such prediction can be assessed by performing local road traffic noise and flow measurements. In a complex system such as an urban zone, traffic noise can extend well beyond the local region where it is generated. In other words, the recorded data at a noise station not only represent the local noise but also the noise from a broader area. Therefore, as a general rule in statistically-based noise maps, like Dynamap, each sensor should be positioned in a site which is mostly uncorrelated with other sensors at short-time scales (few minutes), especially inside its own group. This should be done in order to minimize spurious sensors cross-correlations due to local perturbations. On the contrary, we expect highly correlated behavior between sensors over long-time scales to maintain the similarities within the groups. Indeed, Dynamap predictions are well correlated with the corresponding noise measurements, even at short integration times, when averages over both measurements and predictions inside each group are performed.