Abstract
ABSTRACTRecently, noise pollution has taken place as one of the most human health disorders. The main sources of noise are coming from human malpractices on reckless car driving and the use of loud speakers in different festivals at different places. Behavioural study explores that in many places the local usual road traffic noise level exceeds the normal standards. However, few people have adaptive capacity to ignore the effect of ambient noise pollution within considerable limits. Thus, in this article, we have developed an adaptive traffic noise model over the vulnerable society of a specific noise-prone zone. We develop a fuzzy logic to analyse the noise risk, and then it has been compared by the odds ratio of the experimental data. Moreover, we have considered the normality and non-normality in participation for various noise parameters, namely noise level, exposure time and affected age group of the people of a particular place as well. Finally, graphical illustrations are made for global justification of the model.
Highlights
The modern technology has given us a comfortable life and it becomes increasing with the urge of human beings
Noise pollution has become a major concern of communities living in the vicinity of highways/road corridors, and intersections (Goswami, 2009, 2011; Goswami & Swain, 2012a, 2012b; Goswami, Swain, Mohapatra, & Bal, 2013; Swain & Goswami, 2012, 2013a, 2013b, 2014; Swain, Goswami, & Das, 2013; Swain, Goswami, & Panda, 2012; Swain, Goswami, & Tripathy, 2012; Swain, Panda, & Goswami, 2012)
Note: Noise level standards according to Central Pollution Control Board (CPCB, 2000), India
Summary
The modern technology has given us a comfortable life and it becomes increasing with the urge of human beings. With the help of precautionary principle, the problem of risk management was studied by Cameron and Peloso (2005) The authors such as Haimes (2009) and Takas (2010) have developed several models over multilevel fuzzy approach to risk and disaster management for studying the noise annoyance. Shivdev, Nagarajappa, Lokeshappa, and Kusagur (2015) discussed empirically a noise pollution model considering noise level (N), affected people of different age (A) groups and exposure time duration (T) by the formula R = N × A × T. Utilizing this formula via fuzzy logic control, they were able to find the resultant pollution level and total risk .
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