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

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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Bibliographic Details
Main Author: Kovacevic, Ana (auth)
Other Authors: Urosevic, Vladimir (auth), Kaddachi, Firas (auth)
Format: Electronic Book Chapter
Language:English
Published: InTechOpen 2018
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