Ant Colony Based Architecture For Air Pollution Aware Vehicle Routing In Smart Cities Using Machine Learning

Abstract

The government of India has started the 100 Smart Cities Mission project on 25th June 2015. The smart city is a live-capable, reasonable and flourishing economy offering numerous chances to their kin. The objective of establishing a smart city is to distribute resources efficiently, to improve the communication between citizens and government, to help data-driven decision making, and to reduce environmental footprint, etc. newlineIn smart cities, air pollution hazards are the central issue required to address. According to the WHO report of 2018, around 7 million premature deaths occurred due to air pollution, and more than 91% of the world population lives under severe pollution hazards [1]. To establish meaningful smart cities, it is essential to either reduce air pollution or moderate the impact of air pollution on the human body. But moving towards the zero pollution objective required lots of effort and legislation. newlineOur research aims to reduce the effect of air pollution on the human body by selecting a better path during traveling, especially for the two-wheeler s rider, who suffers from diseases like aggravated cardiovascular, respiratory illness, accelerated aging lungs, asthma, bronchitis, emphysema, etc. Moreover, awareness about the current level of pollution will help them to take preventive actions. newlineWe have proposed ant colony-based architecture for air pollution-aware vehicle routing in smart cities using machine learning to reduce the effect of air pollution on the human body during traveling. newlineThe proposed architecture uses an ant colony algorithm to find the optimal path considering less distance and low air pollution level (in terms of air quality index) towards the destination. We have identified that the ant colony algorithm executes before the tour of the vehicle starts. Thus, it considers the current scenario (i.e., air pollution level and traffic volume) and suggests the optimal path. However, the values of air pollution, traffic volume, etc., changes frequently with time. So, when the vehicle