Detection of Human Activity for Ambient Assisted Living: A SVM Based Approach

  • Rohan MandalEmail author
  • Uday Maji
  • Saurabh Pal
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 12)


This paper proposes a novel approach to discriminate between two similar kinds of human activity which can be useful for ambient assisted living for elderly people. Various human activity detection methods have been developed in last decade, but still ambiguity lies in efficient detection of similar type of activities. This work suggests an efficient way to discriminate between two similar activities walking on a plane surface and climbing on stairs. Support Vector Machine (SVM) classifier is used to quantify the type activity. This method gives classification accuracy of about 90%.


Ambient assisted living (AAL) Activities of daily living (ADL) SVM Activity detection 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Applied Electronics and Instrumentation EngineeringHaldia Institute of TechnologyHaldiaIndia
  2. 2.Department of Applied PhysicsUniversity of CalcuttaKolkataIndia

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