An Implementation of Formal Framework for Collective Systems in Air Pollution Prediction System.

Greater attention to the quality of life forces increased activity in the field of air quality monitoring. Many cities official perceive air pollution as an increasing issue worth investigating and managing. Thus, research focuses on delivering reliable real-time information on pollutants across the city area. The main focus of this article is the presentation of a collective framework to predict air pollution implementation. This solution allows informing about air pollution in places where no meters are available. The experimental results showed that the collective framework emerges the collective members' knowledge and delivers prediction better than any algorithm used for agent predictions. It proves that collectives achieve better results than their members.