The improvement of the quality of life in the framework of the smartcity paradigm cannot be limited to a set of objective measures carried out over several critical parameters (e.g. noise, air pollution). The citizen's perception of the problem to be solved, as well as the perception of the improvement achieved with the policies defined for this purpose, is more important than the objectivity and the measurement of the change achieved. A first auralization approach for the evaluation of the acoustic perception of street noise is presented in this work. The wireless acoustic sensor network can pick up street noise, and can even record specific sounds that reach a higher equivalent level for study, but the most important thing for administration is whether the neighbour has noticed an improvement in the quality of life. This work is a first approximation to an estimation of the real perception of citizens of the street urban noises collected by a low-cost wireless acoustic sensor network.

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.

The impulse response of a piezoelectric transducer can be calculated using the electrical equivalent circuit model with the Manson method for a bandwidth in far field. Nevertheless, these approaches are not sufficiently precise because the importance of homogeneous structure medium where the transducer emit the signal in part determine the bandwidth in which it acts due to the interactions of this with the environment. This paper describes preliminary research results on piezoelectric impulse response measurement in small space, making use of the procedure presented by Angelo Farina for transducers emitting in reverberant spaces. Combination the Basics of Exponential Sine Sweep (ESS) method, techniques of arrival detection and signal processing it is possible to obtain the impulse response in piezoelectric transducer emitting in a homogeneous medium. The propose of this technique is the characterization of the signal produced by a hadron beam in cancer treatments or hadrontherapy, for its corresponding analysis in homogeneous mediums whose characteristics are similar to human tissue.

The data recording of underwater noise is a key aspect for the prevention and improvement of management systems of maritime spaces. Thus, due to the presence of activities potentially generating impulsive noise, the ports deserve special attention. This article describes and shows the results of the spatial monitoring of both the basal noise and the impulsive noise sources present in Port Facilities. A vessel has been equipped with a smart digital hydrophone with a working frequency range between 10 and 200 kHz and an RVR of, approximately, -170 dB @ 1V / µPa. Coupling the acoustic data together with the GPS coordinates of the vessel, a GIS map with the spatiotemporal distribution of the basal sound pressure levels has been made, identifying the sources of impulsive noise of interest and its temporal characteristics. This is a preliminary step for the development of future studies on underwater noise pollution and its potential impact on biodiversity in the environment of Port Facilities with the maximum guarantees possible.

The following paper presents a novel method for the exploitation of urban noise and sound measurement. The overarching objective of this work is to advantageously mine & exploit the information embedded into urban sounds. Effectively contributing to the development of services and products via the advancement of the State of The Art in technology of information and telecommunication.

Traditionally, the grand majority of city and urban noise/sound is measure, analysed and classified with the purpose of drawing appropriate government legislation and regulations aimed at contributing to a healthier environment for humans. Furthermore, noise measurements are often, if not always, measured and processed with dedicated high-end microphones and devices. Costly microphones and processing hardware, often based on limited data samples, limit the extension of the exploitation of the data campaigns. Effectively, the trading of sound-related information is almost often a simple absolute noise level measurement business between a sound expert and a council-like or government-like institution.

With these premises, we can safely say that most of the urban noise and sound business is carried out with the sole purpose of reporting or denouncing, to the appropriate authorities, a misconduct (e.g. noisy streets, bars, cities) or correct a misuse of council resources (e.g. bus re-routing, city planning). Other types of urban noise business activities clearly exist but its span is definitely limited.

We believe that urban sounds do carry more information than what it is extracted to date. The wide availability of powerful AI tools makes it even more true. We believe that urban sound data can be conveniently mined via modern sound algorithm methods. We also believe that in the traditional way of processing urban sound datasets, the employment of costly hardware does represent a limiting factor for the business that can be built around urban sound analysis.

We present a technologically novel method for the capturing, processing and trading of urban sound-based information. The presented method is developed around consumer-grade sound devices that, being relatively inexpensive, can be considered a commodity hardware. An example that we would like to present as such is Echo, the cloud-based commercial multi-microphone smart speaker product by Amazon. Being widely available and easily purchased for US$60 over the Internet, Echo represents a great example of a commodity hardware that can be purchased or rented for virtually no cost.

Unlike traditional urban sound processing systems, we discuss how to move the sound processing algorithms to a cloud-based server. In a way, similarly to what Amazon did with the cloud product Alexa, we propose to decentralize part of the software processing of sound/noise to a more agile cloud-based server. In the following way we will be able to enable the use of these algorithms to a third party via the use of multiple APIs. This will naturally free the consumer-grade sound sensors from the difficult task of processing, making it extremely inexpensive.

In this paper, beside primarily focusing on the scientific aspect of the method, we will like to discuss as well, perhaps in greater details than what it is normally done, the main business scenarios where the presented idea could enable novel and exciting commercial opportunities. Hence, we will show that such a method will open new business models in the area of urban sound analysis and in its exploitation.

The novelty aspects of the approach presented in this proposal is manifold:

1. Instead of using proprietary and costly devices, we propose to explore the use of a consumer-grade commodity hardware for sound capturing and measurement.

2. Develop and implement de-centralized urban sound analysis algorithms for the processing of urban sound samples that are cloud-based. As such, their use will be offered via an edge server and will not depend, or will only marginally depend, on the capabilities of the employed sound capturing device. Effectively making it simpler and cheaper.

3. Build an overall system that is heavily cloud-based (e.g. edge computing)so that the information collected by the inexpensive sound capturing devices can be processed by professional remote sound algorithms, developed by independent experts, via APIs that are accessed following a pay-per-use business scheme.

From the business development point of view, the proposed overall system design structure is the most innovative aspect of this paper. Furthermore, the fact that all processing algorithms are basically cloud-based services, allows us to envision a large number of business cases effectively being enabled by what we propose. A detailed description of such an important aspect is given in further sections.