Anomaly Detection Using RFID-Based Information Management in an IoT Context,Journal of Organizational and End User Computing

当前位置： X-MOL 学术 › Journal of Organizational and End User Computing › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Anomaly Detection Using RFID-Based Information Management in an IoT Context
Journal of Organizational and End User Computing ( IF 3.6 ) Pub Date : 2018-07-01 , DOI: 10.4018/joeuc.2018070101
Raúl Parada ₁ , Joan Melià-Seguí ₂ , Rafael Pous ₃

Affiliation

IoT-basedenvironmentsmayinferanomaliesbasedonthedataprocessedfromtheirheterogeneous sensors. Within the technologies evolving the IoT concept, nowadays the Radio Frequency Identification(RFID)technologyisadefactostandardinareaslikeretailorlogistics.Forinstance, mostretailersattachRFID-labelstotheiritemstoavoidstock-outintheinventoryorspeedupcash processes.Besidesidentification,RFIDprovidesfurtherRFdatawhichcanbeusedforinformation management like anomaly detection (i.e. a shoplifting in a RFID loss prevention system). This manuscriptpresentstwoIoTscenariostodetectanomaliesusingmultivariateoutlierdetectionmethods, uniquelyusingRFIDdata.Thisresearchempiricallyevaluatestheauthors’proposedmethodsby reproducingaRFID-enabledstore,andthetwoproposedscenarios.TheevaluationachievedaFalse PositiveRatearound0.1%andaTruePositiveRatearound87%. KEywORDS Loss Prevention Systems, Machine Learning, Multivariate, Outlier, Radio Frequency Identification

中文翻译：