The DYNAMAP project is aimed at implementing a dynamic noise mapping system able to determine the acoustic impact of road infrastructures in real-time, due to the basis settled by the European Noise Directive 2002/49/EC. A Wireless Acoustic Sensor Network is used to collect the measurements in two pilot areas: in the city of Milan (urban) and in the A90 motorway around Rome (suburban). For a proper evaluation of the road infrastructure noise level, the anomalous noise events (ANE) unrelated to traffic noise (e.g. sirens, horns, speech, doors…) should be removed before updating the noise maps. For this purpose, an anomalous noise events detector (ANED) has been designed using Mel Frequency Cepstral Coefficients (MFCC) and Gaussian Mixture Models (GMM), and trained using data from a real-life recording campaign in the A90. In this work, the preliminary version of the ANED algorithm is adjusted to conform to the requirements of the final 19-node WASN deployed in the suburban environment. The study pays special attention to analyze the characteristics of the acoustic data in real-life conditions and their differences between the 19-nodes in the Rome pilot, in order to adapt the ANED to the entire WASN.