Noise pollution is a critical factor affecting public health, the relationship between road traffic noise (RTN) and several diseases in urban areas being especially disturbing. The Environmental Noise Directive 2002/49/EC and the CNOSSOS-EU framework are the main instruments of the European Union to identify and combat noise pollution, requiring Member States to compose and publish noise maps and noise management action plans every five years. Nowadays, the noise maps are starting to be tailored by means of Wireless Acoustic Sensor Networks (WASN). In order to exclusively monitor the impact of RTN on the well-being of citizens through WASN-based approaches, those noise sources unrelated to RTN denoted as Anomalous Noise Events (ANEs) should be removed from the noise map generation. This paper introduces an analysis methodology considering both Signal-to-Noise Ratio (SNR) and duration of ANEs to evaluate their impact on the A-weighted equivalent RTN level calculation for different integration times. The experiments conducted on 9 h of real-life data from the WASN-based DYNAMAP project show that both individual high-impact events and aggregated medium-impact events bias significantly the equivalent noise levels of the RTN map, making any derived study about public health impact inaccurate.

La Salle and Ebro Observatory have been involved in remote sensing projects in Antarctica for the last 11 years (approximately one solar cycle). The Ebro Observatory has been monitoring and analyzing the geomagnetic and the ionospheric activity in the Antarctic Spanish station Juan Carlos I (ASJI) (62.7°S, 299.6°E) for more than eighteen and ten years, respectively. La Salle has two main goals in the project. The first one is the data transmission and reception from Antarctica to Spain to obtain a historical series of measurements of channel sounding of this 12,760-km ionospheric HF (high frequency) radio link. The second one is the establishment of a stable data low power communication system between the ASJI and Cambrils, Spain (41.0°N, 1.0°E), to transmit the data from the remote sensors located on the island. In this paper, both narrowband and wideband soundings have been carried out to figure out the channel availability performed using a frequency range from 2 to 30 MHz with 0.5 MHz step during the 24 h of the day, encompassing wider channel measurements than previously done, in terms of hours and frequency. This paper presents the results obtained for the austral summer in 2014, using a monopole antenna at the transmitter and an inverted V on the receiver side. These results led us to the final physical layer design for the long Remote Sens. 2015, 7 11713 haul link, dividing the day into two parts: daytime, with low data throughput design, and nighttime, reaching high data throughput.

Traffic noise is presently considered one of the main pollutants in urban and suburban areas. Several recent technological advances have allowed a step forward in the dynamic computation of road-traffic noise levels by means of a Wireless Acoustic Sensor Network (WASN) through the collection of measurements in real-operation environments. In the framework of the LIFE DYNAMAP project, two WASNs have been deployed in two pilot areas: one in the city of Milan, as an urban environment, and another around the city of Rome in a suburban location. For a correct evaluation of the noise level generated by road infrastructures, all Anomalous Noise Events (ANE) unrelated to regular road-traffic noise (e.g., sirens, horns, speech, etc.) should be removed before updating corresponding noise maps. This work presents the production and analysis of a real-operation environmental audio database collected through the 19-node WASN of a suburban area. A total of 156 h and 20 min of labeled audio data has been obtained differentiating among road-traffic noise and ANEs (classified in 16 subcategories). After delimiting their boundaries manually, the acoustic salience of the ANE samples is automatically computed as a contextual Signal-to-Noise Ratio (SNR) together with its impact on the A-weighted equivalent level ( $\Delta L_{Aeq}$ ). The analysis of the real-operation WASN-based environmental database is evaluated with these metrics, and we conclude that the 19 locations of the network present substantial differences in the occurrences of the subcategories of ANE, with a clear predominance of the noise of sirens, trains, and thunder.

Environmental noise is increasing year after year, especially in urban and suburban areas. Besides annoyance, environmental noise also causes harmful health effects on people. The Environmental Noise Directive 2002/49/EC (END) is the main instrument of the European Union to identify and combat noise pollution, followed by the CNOSSOS-EU methodological framework. In compliance with the END legislation, the European Member States are required to publish noise maps and action plans every five years. The emergence of Wireless Acoustic Sensor Networks (WASNs) have changed the paradigm to address the END regulatory requirements, allowing the dynamic ubiquitous measurement of environmental noise pollution. Following the END, the LIFE DYNAMAP project aims to develop a WASN-based low-cost noise mapping system to monitor the acoustic impact of road infrastructures in real time. Those acoustic events unrelated to regular traffic noise should be removed from the equivalent noise level calculations to avoid biasing the noise map generation. This work describes the different approaches developed within the DYNAMAP project to implement an Anomalous Noise Event Detector on the low-cost sensors of the network, considering both synthetic and real-life acoustic data.Moreover, the paper reflects on several open challenges, discussing how to tackle them for the future deployment of WASN-based noise monitoring systems in real-life operating conditions.

One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE) unrelated to road traffic (sirens, horns, people, etc.) should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED). In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap) and low-capacity (Lo-Cap) sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on $\mathsf{\mu }$ Controller-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around $\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$6$}\right.$ of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%). However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection.