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Optimizing pervasive sensor data acquisition utilizing missing values substitution

dc.creatorMichalopoulos, M.en
dc.creatorMaglogiannis, I.en
dc.creatorAnagnostopoulos, C.en
dc.creatorDoukas, C.en
dc.creatorHadjiefthymiades, S.en
dc.date.accessioned2015-11-23T10:39:35Z
dc.date.available2015-11-23T10:39:35Z
dc.date.issued2010
dc.identifier10.1145/1839294.1839308
dc.identifier.isbn9781450300711
dc.identifier.urihttp://hdl.handle.net/11615/30999
dc.description.abstractAcquisition of pervasive sensor data can be often unsuccessful due to power outage at nodes, time synchronization issues, interference, network transmission failures or sensor hardware issues. Such failures can lead to inadequate data delivery to the monitoring applications resulting in erroneous conclusions. This paper presents a missing values substitution framework that addresses the aforementioned issue. The presented framework has been evaluated within a pervasive sensor monitoring environment that collects and transmits patient health related data and results have been presented. Copyright © 2010 ACM.en
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-77956280628&partnerID=40&md5=b6d309b780df731aaca25c8865424a9e
dc.subjectHealthcare data transmissionen
dc.subjectMissing values substitutionen
dc.subjectPervasive sensorsen
dc.subjectData transmissionen
dc.subjectInadequate dataen
dc.subjectMissing valuesen
dc.subjectMonitoring applicationsen
dc.subjectNetwork transmissionen
dc.subjectPatient healthen
dc.subjectPower outageen
dc.subjectSensor dataen
dc.subjectSensor hardwareen
dc.subjectSensor monitoringen
dc.subjectTime synchronizationen
dc.subjectSensorsen
dc.titleOptimizing pervasive sensor data acquisition utilizing missing values substitutionen
dc.typeconferenceItemen


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