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...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | , |
| Format: | Elektronisch Buchkapitel |
| Sprache: | Englisch |
| Veröffentlicht: |
InTechOpen
2018
|
| Schlagworte: | |
| Online-Zugang: | DOAB: download the publication DOAB: description of the publication |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Search Result 1