Predicting air quality in smart city using novel transferlearning based framework

<p>Air quality is a matter of concern these days due to its adverse effect on humanhealth. Multiple new air pollution monitoring and prediction stations are be-ing developed in smart cities to tackle the issue. Recent advanced deep learningtechniques show excellent performance for air quality predictions but need suffi-cient training data for model performance. The data insufficiency issue at a newstation can be resolved using the proposed novel transfer learning-based frame-work to predict pollution concentration at the new station. The prediction abilityat a new station can be significantly enhanced by this effective technology. Theperformance of the model is assessed on various stations in Delhi, India.</p&gt