Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/39205

TítuloDetection of dangerous situations using a smart internet of things system
Autor(es)Lopes, Nuno Vasco
Santos, Henrique
Azevedo, Ana Isabel
Palavras-chaveInternet of things
IoT
dangerous situations
sensor network
child
self-learning algorithm
Data2015
EditoraSpringer International Publishing AG
RevistaAdvances in Intelligent Systems and Computing
Resumo(s)The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/39205
ISBN9783319165271
DOI10.1007/978-3-319-16528-8_36
ISSN2194-5357
Versão da editorahttp://link.springer.com/chapter/10.1007%2F978-3-319-16528-8_36
Arbitragem científicayes
AcessoAcesso restrito autor
Aparece nas coleções:CAlg - Livros e capítulos de livros/Books and book chapters

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