Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/17245
Título: Semantic architecture for sensors
Autor: Gião, João
Sarraipa, João
Jardim-Gonçalves, Ricardo
Palavras-chave: Sensors
Ontologies
FP7-ICT
Projects ICT
Research Subject Categories::TECHNOLOGY::Information technology::Computer science::Software engineering
Research Subject Categories::FORESTRY, AGRICULTURAL SCIENCES and LANDSCAPE PLANNING::Area technology::Remote sensing
Data: Dez-2015
Editora: IET/CICS.NOVA
Citação: Gião, J.; Sarraipa, J.; Jardim-Gonçalves, R. (2015), Semantic Architecture for Sensors, IET Working Papers Series, WPS06/2015, 26 pp.
Relatório da Série N.º: IET Working Papers Series;WPS06/2015
Resumo: Technological progress in recent years and the increase of Internet of things (IoT) in our daily life brought a huge flood of data that can only be handle, processed and exploited in real-time with the help of Information and Communication Technologies (ICT). The ICT is one main element in order to achieve more efficient and sustainable an environment resource management, while the needs of the citizens are satisfied, creating new applications to improve citizen’s quality life. The creation of new systems that allow the acquisition of context information, automatically and transparently, and give that information to decision support systems are important aspects for information societies. In this paper it will be presented the usability and importance of sensors to get information from our environment in order to know what and when happen changes around us as well as the importance of ontologies in the structure and organization of the systems, to acquire new knowledge.
Descrição: Based on the report for the unit “Sociology of New Information Technologies” of the Master on Computer Sciences at FCT/University Nova Lisbon in 2015-16. The responsible of this curricular unit is Prof. António Moniz
Peer review: yes
URI: http://hdl.handle.net/10362/17245
ISBN: 1646-8929
Aparece nas colecções:FCT: IET - Working Paper Series

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