Modeling of chlorination concentration in public fountains by Machine Learning techniques

Abstract: The project dealt with the elaboration of a mathematical algorithm for prediction of the chlorine concentration in ornamental public fountains. The purpose was to optimize the life of pipes and fountain mechanisms while keeping safe levels of water chlorination. IMESAPI provided real measurements of chorination data. Several Machine learning techniques were used to approximate the light pollution, determining the most appropriate in terms of accuracy.
The prediction algorithm was delivered to IMESAPI.