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|Title:||Ten questions concerning active noise control in the built environment||Authors:||Lam, Bhan
|Keywords:||Engineering::Electrical and electronic engineering||Issue Date:||2021||Source:||Lam, B., Gan, W., Shi, D., Nishimura, M. & Elliott, S. (2021). Ten questions concerning active noise control in the built environment. Building and Environment, 200, 107928-. https://dx.doi.org/10.1016/j.buildenv.2021.107928||Project:||CoT-V4-2019-1||Journal:||Building and Environment||Abstract:||Urban noise pollution is an omnipresent but often neglected threat to public health that must be addressed urgently. Passive noise control measures, which are less effective at reducing low-frequency noise and are often bulky and may impede airflow. As evidenced in automobiles, active control of cabin noise has resulted in lighter cars due to reduced passive insulation. Despite its long history and recent popularisation by consumer head- phones, the implementation of active noise control in the built environment is still rare. To date, active noise control (ANC) has been demonstrated, at source, in construction machines and, in the transmission path, in noise barriers. Recent demand for naturally-ventilated buildings has also spurred the development of active control solutions at the receiving end, such as on windows. The ten questions aim to demystify the principles of ANC and highlight areas in which environmental noise can be actively mitigated. Since the implementation of active control in the built environment usually involves multiple stakeholders, operational concerns are addressed. To conclude, research gaps are identified that would enable increased adoption of ANC in the built environment. There is also renewed interest in applying intelligent ANC to tackle environmentally complex applications, such as varying noise levels in the earcup of ANC headphones, particularly with the advent of the low-cost, low-power, highly-efficient embedded electronics; advancing speaker technology; and new impetus from digital signal processing and artificial intelligence Algorithms.||URI:||https://hdl.handle.net/10356/151258||ISSN:||0360-1323||DOI:||10.1016/j.buildenv.2021.107928||Rights:||© 2021 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Journal Articles|
Updated on Oct 18, 2021
Updated on Oct 18, 2021
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