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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| Other Authors: | , |
| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
InTechOpen
2018
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| Online Access: | DOAB: download the publication DOAB: description of the publication |
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