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A survey on anomalous behavior detection for elderly care using dense-sensing networks
journal contribution
posted on 2020-01-01, 00:00 authored by Samundra Deep, Xi Zheng, Chandan KarmakarChandan Karmakar, Dongjin Yu, Len Hamey, Jiong JinFacing the gradual ageing society, elderly people living independently are in need of serious attention. In order to assist them to live in a safer environment, the increasing cost of nursing care and the shortage of health-care workers urges the demand of home-based assisted living in recent times. Therefore, home-based health-care has become an active research domain, particularly the abnormal activities detection involving information and communications technologies. This survey paper highlights this kind of technologies that exist for human anomalous behavior detection. It also reviews and discusses the current research trends, their outcomes and effects in elderly care. Our study is mainly focused on dense sensing network based activities and anomaly detection, which are robust to environment change, non-intrusive, user-friendly in the sense that do not require the occupant to wear any devices. From our study, we observe that employing sensor fusion techniques could significantly increases the efficiency of dense sensing network. In addition, sensor fusion models ensure a high level of robustness and effectiveness compared to the traditional methods.
History
Journal
Communications Surveys and Tutorials, IEEE Communications SocietyVolume
22Issue
1Pagination
352 - 370Publisher
IEEELocation
Piscataway, N.J.Publisher DOI
ISSN
1553-877XeISSN
2373-745XLanguage
engPublication classification
C1 Refereed article in a scholarly journalUsage metrics
Keywords
Anomaly DetectionDense SensingActivity RecognitionSensor FusionScience & TechnologyTechnologyComputer Science, Information SystemsTelecommunicationsComputer ScienceSenior citizensStatisticsMonitoringHUMAN ACTIVITY RECOGNITIONOF-THE-ARTHEALTH-CARESENSOR DATAPHYSICAL-ACTIVITYFALL DETECTIONSMART HOMEFUSIONCONTEXTMODELDistributed Computing
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