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Chapter Temporal Clustering for Behavior Variation and Anomaly Detection from Data Acquired Through IoT in Smart Cities

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In this chapter, we propose a methodology for behavior variation and anomaly detection from acquired sensory data, based on temporal clustering models. Data are collected from five prominent European smart cities, and Singapore, that aim to become fully "elderly-friendly," with the develop...

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Detaylı Bibliyografya
Yazar:	Kovacevic, Ana (auth)
Diğer Yazarlar:	Urosevic, Vladimir (auth), Kaddachi, Firas (auth)
Materyal Türü:	Elektronik Kitap Bölümü
Dil:	İngilizce
Baskı/Yayın Bilgisi:	InTechOpen 2018
Konular:	Data mining temporal clustering, IoT, smart cities, behavior recognition, anomaly detection
Online Erişim:	DOAB: download the publication DOAB: description of the publication
Etiketler:	Etiketle Etiket eklenmemiş, İlk siz ekleyin!

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