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Special Issue "Sound Monitoring Acoustic Sensor Network Design for Urban and Suburban Environments"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 30 November 2021.

Special Issue Editors

Dr. Rosa Ma Alsina-Pagès
E-Mail Website
Guest Editor
GTM—Grup de recerca en Tecnologies Mèdia, La Salle—Universitat Ramon Llull, c/Quatre Camins, 30, 08022 Barcelona, Spain
Interests: acoustic event detection; real-time signal processing; adaptive signal processing; noise monitoring; noise annoyance; impact of noise events
Special Issues and Collections in MDPI journals
Prof. Dr. Giovanni Zambon
E-Mail Website
Guest Editor
Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy
Interests: sound; acoustics; acoustic analysis; acoustic signal processing; noise analysis; sound analysis; consulting; wave propagation; audio signal processing; psychoacoustics; soundscape
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The Environmental Noise Directive (END) requires that a five-year updating of noise maps is carried out, to check and report on changes that have occurred during the reference period. This led last year’s END to deploy several wireless acoustic sensor networks to improve evaluation of the impact of road traffic noise in the cities around the world. Nevertheless, the END opens the door to the analysis of sound taking into account its source. Annoyance is closely related to both the LAeq value (the equivalent value) of a sound and the type of sound (e.g., road traffic noise, music, birdsong, sirens, alarms, works...). Thus, a new generation of acoustic sensor networks should be designed, in order to come a step closer to sound mapping. So far, several noise mapping sensors, networks and platforms have been developed and deployed in some cities and suburban environments. This new approach is devoted to sound, and not just noise (which is usually limited to non-desired sounds). This new wireless acoustic sensor network requires broad knowledge in several disciplines: accurate hardware design for the acoustic sensors; artificial intelligence algorithms to differentiate the sources of noise; network structure design; information management, and graphical user interface design to communicate the results to users. This Special Issue focuses on all the technologies necessary for development of an efficient wireless acoustic sensor network, from the early design stages through to deployment testing, performance, and policy implications. This Special Issue, prepared by two guest editors, describes the latest trends in worldwide WASN design projects aimed at the design and implementation of smart acoustic sensor networks. The focus of the contributions is on good practice, suitable for the design and deployment of intelligent networks in other locations.

Dr. Rosa Ma Alsina-Pagès
Dr. Giovanni Zambon
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

Article
Validation of a Low-Cost Pavement Monitoring Inertial-Based System for Urban Road Networks
Sensors 2021, 21(9), 3127; https://doi.org/10.3390/s21093127 - 30 Apr 2021
Cited by 1 | Viewed by 525
Abstract
Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, a novel inertial sensor-based system is proposed using a low-cost inertial measurement unit (IMU) and a global positioning system [...] Read more.
Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, a novel inertial sensor-based system is proposed using a low-cost inertial measurement unit (IMU) and a global positioning system (GPS) module, which are connected to a Raspberry Pi Zero W board and embedded inside a vehicle to indirectly monitor the road condition. To assess the level of pavement decay, the comfort index awz defined by the ISO 2631 standard was used. Considering 21 km of roads with different levels of pavement decay, validation measurements were performed using the novel sensor, a high performance inertial based navigation sensor, and a road surface profiler. Therefore, comparisons between awz determined with accelerations measured on the two different inertial sensors are made; in addition, also correlations between awz, and typical pavement indicators such as international roughness index, and ride number were also performed. The results showed very good correlations between the awz values calculated with the two inertial devices (R2 = 0.98). In addition, the correlations between awz values and the typical pavement indices showed promising results (R2 = 0.83–0.90). The proposed sensor may be assumed as a reliable and easy-to-install method to assess the pavement conditions in urban road networks, since the use of traditional systems is difficult and/or expensive. Full article
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Article
A Comparative Survey of Feature Extraction and Machine Learning Methods in Diverse Acoustic Environments
Sensors 2021, 21(4), 1274; https://doi.org/10.3390/s21041274 - 11 Feb 2021
Cited by 4 | Viewed by 776
Abstract
Acoustic event detection and analysis has been widely developed in the last few years for its valuable application in monitoring elderly or dependant people, for surveillance issues, for multimedia retrieval, or even for biodiversity metrics in natural environments. For this purpose, sound source [...] Read more.
Acoustic event detection and analysis has been widely developed in the last few years for its valuable application in monitoring elderly or dependant people, for surveillance issues, for multimedia retrieval, or even for biodiversity metrics in natural environments. For this purpose, sound source identification is a key issue to give a smart technological answer to all the aforementioned applications. Diverse types of sounds and variate environments, together with a number of challenges in terms of application, widen the choice of artificial intelligence algorithm proposal. This paper presents a comparative study on combining several feature extraction algorithms (Mel Frequency Cepstrum Coefficients (MFCC), Gammatone Cepstrum Coefficients (GTCC), and Narrow Band (NB)) with a group of machine learning algorithms (k-Nearest Neighbor (kNN), Neural Networks (NN), and Gaussian Mixture Model (GMM)), tested over five different acoustic environments. This work has the goal of detailing a best practice method and evaluate the reliability of this general-purpose algorithm for all the classes. Preliminary results show that most of the combinations of feature extraction and machine learning present acceptable results in most of the described corpora. Nevertheless, there is a combination that outperforms the others: the use of GTCC together with kNN, and its results are further analyzed for all the corpora. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Memetic chains for improving the Local Wireless Sensor Networks Localization in Urban Scenarios
Authors: Hilde Pérez García
Affiliation: Universidad de León
Abstract: Local Positioning Systems (LPS) are supposing an active field of research in the last few years. Its application in harsh environments for high-demanded accuracy applications is allowing the development of technological activities such as autonomous navigation, indoor localization or low-level flights in restricted environments. LPS consists of ad-hoc deployments of sensors which meets the design requirements of each activity. Among LPS, those based on temporal measurements are attracting the higher interest due to their trade-off among accuracy, robustness, availability and costs. The Time Difference of Arrival (TDOA) is extended in the literature for LPS applications and consequently we perform, in this paper, an analysis of the optimal sensor deployment of this architecture for achieving practical results. This is known as the Node Location Problem (NLP) and has been categorized as NP-Hard. Therefore, heuristic solutions such as Genetic Algorithms (GA) or Memetic Algorithms (MA) have been applied in the literature for the NLP. In this paper, we introduce an adaptation of the so-called MA-SW-Chains for its application in the large-scale discrete discontinuous optimization of the NLP in urban scenarios. Our proposed algorithm (MA-VND-Chains) outperforms the GA and the MA of previous proposals for the NLP by 17% and 10% respectively in the accuracy achieved by the TDOA architecture in the urban scenario introduced.

Title: Validation of low-cost pavement monitoring inertial sensor for urban road networks
Authors: Giuseppe Loprencipe
Affiliation: DICEA, Department of Civil, Constructional and Environmental Engineering, Sapienza University of Rome, Via Eudossiana, 18 00184 Rome, Italy
Abstract: Road networks are continuously monitored to evaluate their decay level. Pavement roughness is one of the parameters of road quality that can be measured and it affecting ride quality, driving safety, and fuel consumption. Many reliable systems were developed to measure accurately pavement roughness by means of the longitudinal profiles named profilometers. These devices are mainly used on suburban roads. There is a lack of devices for measuring pavement roughness on urban roads. In the last 10 years, devices and procedures that use an indirect assessment of pavement roughness through the measurement of accelerations inside a moving vehicle have been developed. These measurements can be performed indifferently with specially made systems by putting together an accelerometer and a GPS or using the same sensors available in smartphones. In this study, a vibration-based system is developed by using a low-cost three-axis Micro-Electro-Mechanical Systems accelerometer and a Global Positioning System instrument, which are connected to a Raspberry Pi Zero board and embedded inside a vehicle to monitor indirectly the road condition. To assess the level of pavement decay, the comfort index awz defined by the ISO26131 standard was considered. Considering 25 km of roads, with different levels of pavement decay, validation measures made using the proposed sensor, a pre-assembled inertial measurement unit (IMU), and a Road Surface Profiler (RSP) were performed. Therefore, comparisons between awzs determined with accelerations measured on the proposed sensor and ones of the other more expensive IMU are made; in addition, also correlations between awz and International Roughness Index and Ride Number determined using the proposed sensor and the RSP were performed. The results were shown very good correlations between the awz calculated with the sensor proposed and ones in the other IMU. In addition, the correlations between awz and IRI and RN were showed promising results, considering the use of the proposed sensor as a reliable method to assess the pavements decay in road networks where the use of traditional systems is complicated and/or not cheap.

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