An IoT-Enabled Acoustic Sensing Platform for Noise Pollution Monitoring
Noise pollution is one of the most critical environmental issues that pose multiple adverse effects on urban citizens' health. Noise monitoring and analysis play a vital role in noise management and are crucial for the implementation of noise control strategies. Traditional methods for acoustic...
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th-mahidol.767092022-08-04T15:37:32Z An IoT-Enabled Acoustic Sensing Platform for Noise Pollution Monitoring Dolvara Gunatilaka Mahidol University Computer Science Engineering Noise pollution is one of the most critical environmental issues that pose multiple adverse effects on urban citizens' health. Noise monitoring and analysis play a vital role in noise management and are crucial for the implementation of noise control strategies. Traditional methods for acoustic measurement involve utilizing standardized instruments to manually inspect acoustic scenes, which can be expensive and time-consuming. The emerging IoT (Internet of Things) technology offers a promising solution to automate the acoustic measurement process, and to increase the spatio-temporal coverage of the sensory networks for noise monitoring. In this paper, we present an IoT-enabled acoustic sensing platform consisting of (1) an affordable acoustic sensing device supporting NB-IoT (Narrowband IoT) communication that can continuously measure sound level, and record acoustic events, (2) the back-end system facilitating sensor device management, and acoustic data collection. The low-cost microphones are calibrated to improve their accuracy with a class 2 sound meter. Finally, we assess the performance of the system in terms of reliability, latency, and node energy consumption. 2022-08-04T08:28:14Z 2022-08-04T08:28:14Z 2021-01-01 Conference Paper 2021 IEEE 12th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2021. (2021), 383-389 10.1109/UEMCON53757.2021.9666534 2-s2.0-85125182008 https://repository.li.mahidol.ac.th/handle/123456789/76709 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85125182008&origin=inward |
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Computer Science Engineering Dolvara Gunatilaka An IoT-Enabled Acoustic Sensing Platform for Noise Pollution Monitoring |
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Noise pollution is one of the most critical environmental issues that pose multiple adverse effects on urban citizens' health. Noise monitoring and analysis play a vital role in noise management and are crucial for the implementation of noise control strategies. Traditional methods for acoustic measurement involve utilizing standardized instruments to manually inspect acoustic scenes, which can be expensive and time-consuming. The emerging IoT (Internet of Things) technology offers a promising solution to automate the acoustic measurement process, and to increase the spatio-temporal coverage of the sensory networks for noise monitoring. In this paper, we present an IoT-enabled acoustic sensing platform consisting of (1) an affordable acoustic sensing device supporting NB-IoT (Narrowband IoT) communication that can continuously measure sound level, and record acoustic events, (2) the back-end system facilitating sensor device management, and acoustic data collection. The low-cost microphones are calibrated to improve their accuracy with a class 2 sound meter. Finally, we assess the performance of the system in terms of reliability, latency, and node energy consumption. |
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Mahidol University |
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Mahidol University Dolvara Gunatilaka |
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Conference or Workshop Item |
author |
Dolvara Gunatilaka |
author_sort |
Dolvara Gunatilaka |
title |
An IoT-Enabled Acoustic Sensing Platform for Noise Pollution Monitoring |
title_short |
An IoT-Enabled Acoustic Sensing Platform for Noise Pollution Monitoring |
title_full |
An IoT-Enabled Acoustic Sensing Platform for Noise Pollution Monitoring |
title_fullStr |
An IoT-Enabled Acoustic Sensing Platform for Noise Pollution Monitoring |
title_full_unstemmed |
An IoT-Enabled Acoustic Sensing Platform for Noise Pollution Monitoring |
title_sort |
iot-enabled acoustic sensing platform for noise pollution monitoring |
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2022 |
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https://repository.li.mahidol.ac.th/handle/123456789/76709 |
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