Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/153454
Title: Extracting urban sound information for residential areas in smart cities using an end-to-end IoT system
Authors: Tan, Ee-Leng
Karnapi, Furi Andi
Ng, Linus Junjia
Ooi, Kenneth
Gan, Woon-Seng
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Tan, E., Karnapi, F. A., Ng, L. J., Ooi, K. & Gan, W. (2021). Extracting urban sound information for residential areas in smart cities using an end-to-end IoT system. IEEE Internet of Things Journal, 8(18), 14308-14321. https://dx.doi.org/10.1109/JIOT.2021.3068755
Project: MOE2017-T2-2-060
Journal: IEEE Internet of Things Journal 
Abstract: With rapid urbanization comes the increase of community, construction, and transportation noise in residential areas. The conventional approach of solely relying on sound pressure level (SPL) information to decide on the noise environment and to plan out noise control and mitigation strategies is inadequate. This paper presents an end-to-end IoT system that extracts real-time urban sound metadata using edge devices, providing information on the sound type, location and duration, rate of occurrence, loudness, and azimuth of a dominant noise in nine residential areas. The collected metadata on environmental sound is transmitted to and aggregated in a cloud-based platform to produce detailed descriptive analytics and visualization. Our approach in integrating different building blocks, namely, hardware, software, cloud technologies, and signal processing algorithms to form our real-time IoT system is outlined. We demonstrate how some of the sound metadata extracted by our system are used to provide insights into the noise in residential areas. A scalable workflow to collect and prepare audio recordings from nine residential areas to construct our urban sound dataset for training and evaluating a location-agnostic model is discussed. Some practical challenges of managing and maintain a sensor network deployed at numerous locations are also addressed.
URI: https://hdl.handle.net/10356/153454
ISSN: 2327-4662
DOI: 10.1109/JIOT.2021.3068755
Rights: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/JIOT.2021.3068755
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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