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Noise is a universal problem that is particularly prominent in developing nations like India. Short-term noise-sensitive events like New Year's Eve, derby matches, DJ night, Diwali night (celebration with firecracker) in India, etc. create lots of noise in a short period. There is a need to come up with a system that can predict the noise level for an area for a short period indicating its detailed variations. GIS (Geographic Information System)-based google maps for terrain data and crowd-sourced or indirect collection of noise data can overcome this challenge to a great extent. Authors have tried to map the highly noisy Diwali night for Lucknow, a northern city of India. The mapping was done by collecting the data from 100 points using the noise capture app (30% were close to the source and 70% were away from the source (receiver). Noise data were predicted for 750 data points using the modeling interpolation technique. A noise map is generated for this Diwali night using the crowd-sourcing technique for Diwali night. The results were also varied with 50 test points and are found to be within ±4.4 dB. Further, a noise map is also developed for the same site using indirect data of noise produced from the air pollution open-sourced data. The produced noise map is also verified with 50 test points and found to be ±6.2 dB. The results are also corroborated with the health assessment survey report of the residents of nearby areas. [ABSTRACT FROM AUTHOR]