Poojah G., Kanishkha L. D., Raj Vignesh K., Edna Elizabeth N., Kaythry P.
Dynamic Vehicular Routing with Pollution Metric using Internet of Things
Vehicular exhausts are the root cause of air pollution in every major city around the world. According to the Environmental Protection Agency (EPA), motor vehicles contribute to 75 percent of Carbon Monoxide (CO) pollution in the United States. Pollutants from automobiles, like CO, compounds of Oxides of Nitrogen (NOx) etc., are all major contributors to the overall air pollution of the environment. Air pollution monitoring is practiced by power plants, which is a very expensive activity. The objective of this work is to navigate the least polluted routes for automobiles to reach the desired destination at a minimal cost.To achieve the goal and to reduce the cumulative pollution caused by automobiles, sensors are used to compute the magnitude of the air pollution in an automobile-intensive area. The pollution data collected by the sensors is sent to a cloud-based platform known as Firebase. Subsequently, a mobile application created using Android Studio is used to integrate the Firebase data and Google Maps.The novelty of this paper is to find the route dynamically which has the least pollution level, using the developed android application.
Arduino, Firebase, Google Maps, Android Studio, IoT
Cite this paper
Poojah G., Kanishkha L. D., Raj Vignesh K., Edna Elizabeth N., Kaythry P.. (2022) Dynamic Vehicular Routing with Pollution Metric using Internet of Things. International Journal of Internet of Things and Web Services, 6, 1-8