Residential noise analysis
Noise pollution, specifically inter-floor noise pollution, has presented itself as a pressing concern in residential buildings, causing reduced quality of life as well as social friction amongst neighbors. This is a result of the rapid urbanization and environmental challenges within our urban lands...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/181752 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Noise pollution, specifically inter-floor noise pollution, has presented itself as a pressing concern in residential buildings, causing reduced quality of life as well as social friction amongst neighbors. This is a result of the rapid urbanization and environmental challenges within our urban landscape. This project aims to cover the complexities of inter-floor noise and its analysis. Examples of inter-floor noise would include impact from basketballs, furniture movement and other structural or household vibrations and noises. Through the usage of vibration sensors and the analysis of the acoustical data captured, the noise types and their respective characteristics are captured and carefully interpreted. Earlier research teams have gathered some pertinent data, which will be leveraged upon in this project for the purposes of processing, synchronizing and analyzing the raw acoustical information. Some areas of focus within this project would be the data conversion and sanitization as well as deep analysis using advanced software such as MATLAB, ArtemiS Suite version 11, Audacity and Excel Workbook.
Furthermore, this project aims to establish robust datasets through sanitization and optimize data analysis frameworks, through which the noise sources are able to be classified effectively. At a first glance, some areas for improvement would include the quality of both the sensor as well as the resulting dataset collected. This would in turn enable an increased accuracy during classification and the overall efficiency of the system. In the future, studies may cover larger datasets as well as a more comprehensive and over-arching noise evaluation, which potentially could determine new and improved strategies when it comes to managing noise in urban residential environments. |
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