Wireless sensor sequence data model for smart home and IoT data analytics

dc.contributor.author Suryadevara, Nagender Kumar
dc.date.accessioned 2022-03-27T05:57:39Z
dc.date.available 2022-03-27T05:57:39Z
dc.date.issued 2017-01-01
dc.description.abstract In this paper, Wireless sensor sequence data mining model is demonstrated for the smart home and Internet of Things data analytics. Exploration of the sensor data patterns by correlating with the multi stream sensor data that are fused from the wireless sensor network is presented. The effective realization of the sensor data patterns from heterogeneous sensing systems for various applications of IoT can be known from the proposed conceptual data model. The conceptual data model includes the discovering of frequent pattern item sets using various computational archetypal. Results of the explicit patterns augmented for data analytics are encouraging as the prototype was tested through real-time data rather than test bed scenario data or synthetic data.
dc.identifier.citation Advances in Intelligent Systems and Computing. v.507
dc.identifier.issn 21945357
dc.identifier.uri 10.1007/978-981-10-2471-9_43
dc.identifier.uri http://link.springer.com/10.1007/978-981-10-2471-9_43
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8931
dc.subject Activities of daily living
dc.subject Data analytics
dc.subject Internet of things
dc.subject Smart home
dc.subject Wellness
dc.subject Wireless sensor networks
dc.title Wireless sensor sequence data model for smart home and IoT data analytics
dc.type Book Series. Conference Paper
dspace.entity.type
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