Abstract Body

With the development of urban areas and the growth of roads and road use, either in public transit or in personal transit, air pollution comes with it. On the other hand, there are not many solutions to the large percentage of pollution occurring from motor vehicles. One of the many reasons for this is that traffic growth data is challenging to process and manage. After detailed research on the current issues regarding public and private transportation in major cities around the world and their effect on our environment, this study aims to create an adaptive computer model that can give insights and allow us to establish new procedures and protocols to achieve Net-Zero carbon emissions. The model that we created will fetch important data regarding traffic patterns, volume, emissions, and other factors such as Electric Vehicles' growing popularity. Our model is fully generic and can be used with any city open data APIs. It will then analyze and discover the crucial features that will help identify critical problems in the areas of transportation that need to be dealt with in the first place. It will also display the correlation between traffic growth and increased air pollution in our cities. Finally, data will be fully visualized to provide fast access and easy comparison between various solutions to the problem.