An Application of linear Regression on Air Pollution Detection Using Deep Learning

A regularly expanding number of urban occupants think about the criticalness of the air quality to their prosperity, especially who are living in the colossal urban territories are genuinely sabotaged through air pollution. Air quality observing assumes an undeniably significant job in giving exact air contamination information to evaluating the effects of air contamination on general wellbeing. Advancement of appropriate sensor systems, by sending the correct air contamination sensors at the ideal put in, so as to address the issues of various gatherings in the city and give the genuinely necessary open administrations, merits cautious consideration, particularly when savvy city improvement is to be measured. Notwithstanding, air quality observation is an exorbitant degree. To handle such a test, air contamination sensor position can be deliberately intended to accomplish definite ideal resident driven goals without field data, and application of the linear regression to it.