Implementation of Digital Carbon Footprint Emission Estimator and Predictor for Mobile Devices

With the surge in digitalization and the increasing usage of technology, there has been a significant increase in the digital carbon footprint. General people at least have some kind of awareness about the carbon footprint generated by industries, fuel consumption etc. But many people even do not think about how their mobile phones are contributing to generating a special kind of carbon footprint called digital carbon footprint. This paper proposes an application that aims to detect the screen time of different apps of an individual user, thereby calculating and accounting for the overall carbon footprint of the user. To predict the future carbon footprint a user can generate, a machine learning model was designed. The major objective of this study is to explore the various sources and gather information about the digital carbon footprint generated by different mobile applications, measuring the screen time of individual applications and thus calculating the digital carbon footprint. The application generates the digital carbon footprint of individual application as well as show the cumulative value of the digital carbon footprint by considering the contribution of all application and predicting their future value of it.