Assessment of noise levels by using noise prediction modeling

Published

30-09-2023

DOI:

https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.3.54

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Issue

Section

Research article

Authors

  • Santosh Kumar Sahu Veer Surendra Sai University of Technology
  • B. R. Senthil kumar
  • Y. Aboobucker parvez
  • Ashish Verma

Abstract

The third-most dangerous type of pollution, after air and water pollution, according to the World Health Organization, is noise pollution. Brief and prolonged exposure to noise pollution can have negative consequences on people, including psychological disorders, including anxiety and depression, hypertension, hormonal imbalances, and a rise in blood pressure that can result in cardiovascular disease. The WHO estimates that up to 40% of individuals in Europe are currently exposed to loud noises. This study makes an effort to predict noise levels in and around the School of Architecture and Planning (SAP) campus using data on traffic volume and flow, vehicle speed, and geometric mean of the road. Additionally, it does a comparison between the expected and actual noise levels and offers workable noise reduction techniques. A mathematical model that takes into consideration has been used to forecast the equivalent noise level. By comparing the expected and actual noise levels, it was found that all values are beyond the permitted limits. Five different locations within SAP were used to assess the amount of noise present. The Lobby recorded the highest and lowest noise levels, respectively, at 75.63 and 74.15 dB (A). There were 73.05, 71.01, 71.81, and 70.5 dB (A) accordingly as the strongest noises in the classroom and auditorium. The maximum noise levels in the library was 63.76 and 64.54 dB (A), respectively. A maximum noise level of 75.29 and 68.14 dB (A) was recorded for the studio.

How to Cite

Santosh Kumar Sahu, B. R. Senthil kumar, Y. Aboobucker parvez, & Ashish Verma. (2023). Assessment of noise levels by using noise prediction modeling. The Scientific Temper, 14(03), 909–915. https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.3.54

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