@techreport{elediasc12725,
            year = {2017},
       publisher = {University of Trento},
          author = {F. Viani and A. Polo and P. Garofalo and N. Anselmi and M. Salucci and E. Giarola},
           title = {An Innovative Technique for Smart Lighting in Buildings through Multi-Objective Particle Swarm Optimization},
            type = {Technical Report},
        keywords = {Smart Buildings, Energy-Efficient Buildings, Smart Lighting, WSN, Automatic Control, Evolutionary Optimization, Multi-Objective PSO},
             url = {http://www.eledia.org/students-reports/725/},
        abstract = {The smart control of lighting in modern buildings is a key feature in order to improve as much as possible the comfort of the persons as well as to reduce the overall energy consumption. Within this framework, this work presents an  innovative technique for the smart lighting of buildings based on the distributed sensing capabilities of a low-cost wireless sensor network (WSN). The acquired information by the WSN nodes is processed by a central unit in order to adaptively control the intensity of lights starting from the real-time measurement of the brightness conditions and energy consumption. A multi-objective evolutionary algorithm based on the particle swarm optimizer (PSO) is exploited in order to minimize a suitable cost function accounting for conflicting user-defined requirements. The effectiveness of the proposed methodology is assessed through a set of laboratory-controlled experiments.}
}