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 development and d...

Full description

Bibliographic Details

Main Authors:	Kovacevic, Ana, Urosevic, Vladimir, Kaddachi, Firas
Format:	Online
Language:	English
Published:	InTechOpen 2021
Subjects:	temporal clustering, IoT, smart cities, behavior recognition, anomaly detection thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining
Online Access:	ONIX_20210602_10.5772/intechopen.75203_392
Tags:	Add Tag No Tags, Be the first to tag this record!