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...
में बचाया:
मुख्य लेखक: | Kovacevic, Ana (auth) |
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अन्य लेखक: | Urosevic, Vladimir (auth), Kaddachi, Firas (auth) |
स्वरूप: | इलेक्ट्रोनिक पुस्तक अध्याय |
भाषा: | अंग्रेज़ी |
प्रकाशित: |
InTechOpen
2018
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विषय: | |
ऑनलाइन पहुंच: | DOAB: download the publication DOAB: description of the publication |
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Chapter Temporal Clustering for Behavior Variation and Anomaly Detection from Data Acquired Through IoT in Smart Cities
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