Comparative study of BSO and GA for the optimizing energy in ambient intelligence

  • Authors:

  • Wendoly J. Gpe. Romero-Rodríguez;Victor Manuel Zamudio Rodríguez;Rosario Baltazar Flores;Marco Aurelio Sotelo-Figueroa;Jorge Alberto Soria Alcaraz

  • Affiliations:

  • Division of Research and Postgraduate Studies, Leon Insitute of Technology, León, México;Division of Research and Postgraduate Studies, Leon Insitute of Technology, León, México;Division of Research and Postgraduate Studies, Leon Insitute of Technology, León, México;Division of Research and Postgraduate Studies, Leon Insitute of Technology, León, México;Division of Research and Postgraduate Studies, Leon Insitute of Technology, León, México

  • Venue:
  • MICAI'11 Proceedings of the 10th international conference on Artificial Intelligence: advances in Soft Computing - Volume Part II
  • Year:
  • 2011

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Abstract

One of the concerns of humanity today is developing strategies for saving energy, because we need to reduce energetic costs and promote economical, political and environmental sustainability. As we have mentioned before, in recent times one of the main priorities is energy management. The goal in this project is to develop a system that will be able to find optimal configurations in energy savings through management light. In this paper a comparison between Genetic Algorithms (GA) and Bee Swarm Optimization (BSO) is made. These two strategies are focus on lights management, as the main scenario, and taking into account the activity of the users, size of area, quantity of lights, and power. It was found that the GA provides an optimal configuration (according to the user's needs), and this result was consistent with Wilcoxon's Test.