A hardware and software system was devised for solving a problem related to energy losses in public lighting services. A computational intelligence framework based on heterogeneous feature models, feature extraction and selection is used for classifying lamp types and wattages. This paper shows how radiometric sensors and lamp image data are used for the classification task. It is also presented an experimental comparison on the public lighting problem domain between three feature selection algorithms.