Activity and anomaly detection in smart home

a survey

U. A. B. U. A. Bakar, Hemant Ghayvat, S. F. Hasanm, S. C. Mukhopadhyay*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

33 Citations (Scopus)

Abstract

Activity recognition is a popular research area with a number of applications, particularly in the smart home environment. The unique features of smart home sensors have challenged traditional data analysis methods. However, the recognition of anomalous activities is still immature in the smart home when compared with other domains such as computer security, manufacturing defect detection, medical image processing, etc. This chapter reviews smart home’s dense sensing approaches, an extensive review from sensors, data, analysis, algorithms, prompting reminder system, to the recent development of anomaly activity detection.

Original languageEnglish
Title of host publicationSmart Sensors, Measurement and Instrumentation
EditorsSubhas Chandra Mukhopadhyay
Place of PublicationSwitzerland
PublisherSpringer, Springer Nature
Pages191-220
Number of pages30
Volume16
ISBN (Electronic)9783319216713
ISBN (Print)9783319216706
DOIs
Publication statusPublished - 2016
Externally publishedYes

Publication series

NameSmart Sensors, Measurement and Instrumentation
Volume16
ISSN (Print)2194-8402
ISSN (Electronic)2194-8410

Fingerprint Dive into the research topics of 'Activity and anomaly detection in smart home: a survey'. Together they form a unique fingerprint.

  • Cite this

    Bakar, U. A. B. U. A., Ghayvat, H., Hasanm, S. F., & Mukhopadhyay, S. C. (2016). Activity and anomaly detection in smart home: a survey. In S. C. Mukhopadhyay (Ed.), Smart Sensors, Measurement and Instrumentation (Vol. 16, pp. 191-220). (Smart Sensors, Measurement and Instrumentation; Vol. 16). Switzerland: Springer, Springer Nature. https://doi.org/10.1007/978-3-319-21671-3_9