Students' Projects
Machine Learning Enabled Pollution Aware Route
| Department | Computer Engineering |
| Year | 2019-20 |
| Budget | 5200 |
| Students | Dhrumin Thakkar |
| Mentor | Prof. Jitendra Bhatia, Prof. Uttam chauhan |
| Abstract | The number of vehicles is increasing exponentially with the rise in technological advancements in automobile industries. Road transport accounts for a significant portion of air pollution in cities and towns, causing problems like smog that lead to serious health issues. Traffic fumes contain harmful chemicals and gases that pollute the atmosphere and contribute to global warming. Traffic congestion increases vehicle emission and results in poor ambient air quality, and recent studies have shown access morbidity and mortality for drivers, commuters and individuals living near major roadways. Since a majority of vehicles are usually driven in densely populated areas, the pollution caused by vehicles greatly endangers human life. As the environmental pollution problem has aroused more and more attention from the public, there is an increasing need to control and manage vehicle density and traffic and also inform citizens regarding the ambient air quality in order to reduce the risk of health problems. Our project offers a solution to the above mentioned problem by providing functionalities such as intelligent decision mining based on air pollution statistical information, furnishing real-time air quality statistics to citizens, and alternative route recommendation to citizens suffering from diseases caused due to air pollution. It automates the process of air pollution monitoring as well as pollution free route recommendation through a system that is capable of AQI calculation and informing citizens regarding the air conditions on a particular day. Thus, the three primary focus areas of this project are traffic management, environment and health. This innovation also aims to distribute the traffic across the overall routes to maintain a sustainable environment. |