The rapid development of urbanization and industrialization led to the suffering of many developing countries from heavy air pollution. The rowing concern for air pollution has been raised by many governments and people worldwide because it affects human health and sustainable development. Particularly, in India, the drastically deteriorating air quality threatens the health of its people. Meanwhile, in smart cities, knowledge of timely and reliable levels of air pollution is essential for the effective setup of smart pollution systems. The method uses the Artificial Neural Network-Linear Vector Quantization (ANN-LVQ). It is an integration of the NN with LVQ, a significant Air Prediction Technique. The main aim of implementing this method is to provide early warnings by predicting air quality and estimate the influencing pollutant that contaminates the quality of air which thereby leads to air pollution. The performances of the methodologies proposed for this model is assessed in terms of accuracy, precision and recall.