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...
Shranjeno v:
Glavni avtor: | Kovacevic, Ana (auth) |
---|---|
Drugi avtorji: | Urosevic, Vladimir (auth), Kaddachi, Firas (auth) |
Format: | Elektronski Book Chapter |
Jezik: | angleščina |
Izdano: |
InTechOpen
2018
|
Teme: | |
Online dostop: | DOAB: download the publication DOAB: description of the publication |
Oznake: |
Označite
Brez oznak, prvi označite!
|
Podobne knjige/članki
-
Chapter Temporal Clustering for Behavior Variation and Anomaly Detection from Data Acquired Through IoT in Smart Cities
od: Kovacevic, Ana
Izdano: (2018) -
DevOps for Trustworthy Smart IoT Systems
Izdano: (2021) -
DevOps for Trustworthy Smart IoT Systems
Izdano: (2021) -
Smart Sensor Technologies for IoT
Izdano: (2021) -
IoT Multi Sensors
Izdano: (2023)