JOURNAL ARTICLE

Classification Algorithms In Human Activity Recognition Using Smartphones

Mohd Fikri Azli Bin AbdullahNegara, Ali Fahmi PerwiraMd. Shohel SayeedDeok-Jai ChoiKalaiarasi Sonai Muthu

Year: 2012 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

Rapid advancement in computing technology brings computers and humans to be seamlessly integrated in future. The emergence of smartphone has driven computing era towards ubiquitous and pervasive computing. Recognizing human activity has garnered a lot of interest and has raised significant researches- concerns in identifying contextual information useful to human activity recognition. Not only unobtrusive to users in daily life, smartphone has embedded built-in sensors that capable to sense contextual information of its users supported with wide range capability of network connections. In this paper, we will discuss the classification algorithms used in smartphone-based human activity. Existing technologies pertaining to smartphone-based researches in human activity recognition will be highlighted and discussed. Our paper will also present our findings and opinions to formulate improvement ideas in current researches- trends. Understanding research trends will enable researchers to have clearer research direction and common vision on latest smartphone-based human activity recognition area.

Keywords:
Activity recognition Ubiquitous computing Range (aeronautics) Information technology Statistical classification Key (lock)

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Topics

Context-Aware Activity Recognition Systems
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Human Pose and Action Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Human Mobility and Location-Based Analysis
Social Sciences →  Social Sciences →  Transportation

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