2026-09-16T09:19:07Zhttps://gredos.usal.es/oai/request

oai:gredos.usal.es:10366/1351562025-04-30T20:38:32Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134811

García, Elena Rodríguez González, Sara De Paz, Juan F. Bajo Pérez, Javier 2017-09-06T09:17:06Z 2017-09-06T09:17:06Z 2014 Distributed Computing and Artificial Intelligence, 11th International Conference Advances in Intelligent Systems and Computing. pp. 195-207. 978-3-319-07592-1 (Print) / 978-3-319-07593-8 (Online) 2194-5357 (Print) / 2194-5365 (Online) http://hdl.handle.net/10366/135156 This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optimization both energy consumption and economically from a modular architecture and fully adaptable to the current lighting systems possible. The architecture has been tested and validated successfully and continues its development today. en info:eu-repo/semantics/openAccess Computer Science Intelligent Lighting Control System info:eu-repo/semantics/conferenceObject