Comparative Study of BSO and GA for the Optimizing Energy in Ambient Intelligence

• Published in: Advances in Soft Computing pp. 177 - 188
• Main Authors: Romero-Rodríguez, Wendoly J. Gpe, Zamudio Rodríguez, Victor Manuel, Baltazar Flores, Rosario, Sotelo-Figueroa, Marco Aurelio, Alcaraz, Jorge Alberto Soria
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Ambient Intelligence; BSO; Energy Management
• ISBN: 9783642253294; 3642253296
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-25330-0_16

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.