Activity and Anomaly Detection in Smart Home: A Survey

  • U. A. B. U. A. Bakar
  • Hemant Ghayvat
  • S. F. Hasanm
  • S. C. MukhopadhyayEmail author
Part of the Smart Sensors, Measurement and Instrumentation book series (SSMI, volume 16)


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.


Support Vector Machine Hide Markov Model Gaussian Mixture Model Activity Recognition Anomaly Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • U. A. B. U. A. Bakar
    • 1
  • Hemant Ghayvat
    • 1
  • S. F. Hasanm
    • 1
  • S. C. Mukhopadhyay
    • 1
    Email author
  1. 1.School of Engineering and Advanced TechnologyMassey UniversityPalmerston NorthNew Zealand

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