Show simple item record

dc.contributor.authorTapia Martínez, Dante I.
dc.contributor.authorAlonso Rincón, Ricardo Serafín 
dc.contributor.authorPrieta Pintado, Fernando de la 
dc.contributor.authorZato Domínguez, Davinia Carolina
dc.identifier.citationFuzzy Systems (FUZZ), 2010 IEEE International Conference on.
dc.description.abstractThe significance that Ambient Intelligence (AmI) has acquired in recent years requires the development of innovative solutions. Nonetheless, the development of AmI-based systems requires the creation of increasingly complex and flexible applications. In this regard, the use of context-aware technologies is an essential aspect in these developments to perceive stimuli from the context and react upon it autonomously. This work presents a novel platform that defines a method for integrating dynamic and self-adaptable heterogeneous Wireless Sensor Networks (WSNs). This approach facilitates the inclusion of context-aware capabilities when developing intelligent ubiquitous systems, where functionalities can communicate in a distributed way. Furthermore, the information obtained must be managed by intelligent and self-adaptable technologies to provide an adequate interaction between the users and their environment. Agents and Multi-Agent Systems are one of these technologies. The agents have characteristics such as autonomy, reasoning, reactivity, social abilities and pro-activity which make them appropriate for developing dynamic and distributed systems based on AmI. This way, the integration of the platform with a Service-Oriented Multi-Agent architecture is proposed. Finally, conclusions and future work are presented.
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.subjectComputer Science
dc.titleSYLPH: An Ambient Intelligence based platform for integrating heterogeneous Wireless Sensor Networks

Files in this item


This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs 3.0 Unported
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported