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dc.contributor.authorDe, Suparna
dc.contributor.authorBermúdez Edo, María del Campo 
dc.contributor.authorWang, Wei
dc.date.accessioned2024-11-25T07:32:34Z
dc.date.available2024-11-25T07:32:34Z
dc.date.issued2024
dc.identifier.citationDe, S., Wang, W., Bermudez-Edo, M. (2024). Data Models and Contextual Information. In: Ziegler, S., Radócz, R., Quesada Rodriguez, A., Matheu Garcia, S.N. (eds) Springer Handbook of Internet of Things. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-031-39650-2_16es_ES
dc.identifier.urihttps://hdl.handle.net/10481/97293
dc.description.abstractThe Internet of Things (IoT) and its applications emphasize the need for being context-aware to be able to sense the changing environmental conditions and to make use of the rich contextual information for analysis. The huge volume and high-velocity characteristics of IoT data necessitates that representation of IoT data takes into consideration the contextual information at scale during every step of the data processing life cycle, from production to storage, publication, and search. This chapter categorizes and describes the diverse forms of IoT data that are obtained from heterogeneous sensing sources. It also presents a framework for describing and analyzing the different types of contextual information that need to be associated with the IoT data in order to drive context-aware management and intelligent analytics. In addition, mechanisms for storing big IoT data and its contextual information are described, and common search and discovery methods for making IoT data accessible to applications and analysis components are presented.es_ES
dc.language.isoenges_ES
dc.publisherSpringeres_ES
dc.relation.ispartofseriesSpringer Handbook of Internet of Things;
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licensees_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es_ES
dc.titleData Models and Contextual Informationes_ES
dc.typebook partes_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doihttps://doi.org/10.1007/978-3-031-39650-2_16
dc.type.hasVersionAMes_ES


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