In urban areas, the levels of air pollution play a significant role in the quality of life. These levels are rapidly increasing due to exponential urbanization. Although the field of real-time monitoring and forecasting of air pollution levels by fusing multiple modalities has been studied extensively, there is limited work on considering environmental audio in this fusion process. Moreover, studies on developed systems for noise pollution capturing and environmental sound classification have not investigated the potential compression of this considerable type of information. In the present work, a unified system for capturing and classifying urban environmental sounds is developed. Edge devices responsible for audio capturing (mobile phones, IoT nodes), compress the collected data and upload it to the Cloud. A server is then obliged for classifying this information to reveal its correlation with air pollution. We report a robust Auto-Encoder for Urban Environmental Audio Compression and Reconstruction, while the system’s performance on classification is very simillar to this of a State-of-the-Art classifier.

Authors: Emvoliadis, Alexandros; Vryzas, Nikolaos; Stamatiadou, Marina Eirini; Vrysis, Lazaros; Dimoulas, Charalampos; Drosou, Anastasios;Tzovaras, Dimitrios
Affiliations: Information Technologies Institute (ITI), Centre of Research and Technology Hellas (CERTH), Thermi-Thessaloniki, Greece; Aristotle University of Thessaloniki, Thessaloniki, Greece; Aristotle University of Thessaloniki, Thessaloniki, Greece; Aristotle University of Thessaloniki, Thessaloniki, Greece; Information Technologies Institute (ITI), Centre of Research and Technology Hellas (CERTH), Thermi-Thessaloniki, Greece; Information Technologies Institute (ITI), Centre of Research and Technology Hellas (CERTH), Thermi-Thessaloniki, Greece(See document for exact affiliation information.)
Express Paper 80; AES Convention 154; May 2023
Publication Date: May 13, 2023 Import into BibTeX
Subject: Acoustics & Speech
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=22105

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