A framework of personal data analytics for well-being oriented life support

Seiji Kasuya; Xiaokang Zhou; Shoji Nishimura; Qun Jin

doi:10.1007/978-3-662-47895-0_53

A framework of personal data analytics for well-being oriented life support

Seiji Kasuya^*, Xiaokang Zhou, Shoji Nishimura, Qun Jin

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

Nowadays, we are living in a well-suited social environment with a variety of lifestyles and values. Life support has become important in such a diversified society. Along with continuously collecting the tremendous amount of personal big data generated in the social environment, it is possible for us to provide the life support based on personal data analytics. Moreover, analyzing such a kind of data can facilitate deep understanding of individual life. In this study, we focus on personal data analytics to support well-being oriented life. Three categories of personal data are classified from the collection of individuals’ daily life data, and a framework of well-being oriented personal data analysis is proposed, which can provide people with suggestions and advices to improve their living life.

Original language	English
Title of host publication	Lecture Notes in Electrical Engineering
Publisher	Springer Verlag
Pages	443-449
Number of pages	7
Volume	354
ISBN (Print)	9783662478943
DOIs	https://doi.org/10.1007/978-3-662-47895-0_53
Publication status	Published - 2016
Event	10th International Conference on Future Information Technology, FutureTech 2015 - Hanoi, Viet Nam Duration: 2015 May 18 → 2015 May 20

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	354
ISSN (Print)	18761100
ISSN (Electronic)	18761119

Other

Other	10th International Conference on Future Information Technology, FutureTech 2015
Country/Territory	Viet Nam
City	Hanoi
Period	15/5/18 → 15/5/20

Keywords

Big data analysis
Personal data
Well-Being oriented life support

ASJC Scopus subject areas

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-3-662-47895-0_53

Cite this

Kasuya, S, Zhou, X, Nishimura, S & Jin, Q 2016, A framework of personal data analytics for well-being oriented life support. in Lecture Notes in Electrical Engineering. vol. 354, Lecture Notes in Electrical Engineering, vol. 354, Springer Verlag, pp. 443-449, 10th International Conference on Future Information Technology, FutureTech 2015, Hanoi, Viet Nam, 15/5/18. https://doi.org/10.1007/978-3-662-47895-0_53

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abstract = "Nowadays, we are living in a well-suited social environment with a variety of lifestyles and values. Life support has become important in such a diversified society. Along with continuously collecting the tremendous amount of personal big data generated in the social environment, it is possible for us to provide the life support based on personal data analytics. Moreover, analyzing such a kind of data can facilitate deep understanding of individual life. In this study, we focus on personal data analytics to support well-being oriented life. Three categories of personal data are classified from the collection of individuals{\textquoteright} daily life data, and a framework of well-being oriented personal data analysis is proposed, which can provide people with suggestions and advices to improve their living life.",

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AU - Zhou, Xiaokang

AU - Nishimura, Shoji

AU - Jin, Qun

PY - 2016

Y1 - 2016

N2 - Nowadays, we are living in a well-suited social environment with a variety of lifestyles and values. Life support has become important in such a diversified society. Along with continuously collecting the tremendous amount of personal big data generated in the social environment, it is possible for us to provide the life support based on personal data analytics. Moreover, analyzing such a kind of data can facilitate deep understanding of individual life. In this study, we focus on personal data analytics to support well-being oriented life. Three categories of personal data are classified from the collection of individuals’ daily life data, and a framework of well-being oriented personal data analysis is proposed, which can provide people with suggestions and advices to improve their living life.

AB - Nowadays, we are living in a well-suited social environment with a variety of lifestyles and values. Life support has become important in such a diversified society. Along with continuously collecting the tremendous amount of personal big data generated in the social environment, it is possible for us to provide the life support based on personal data analytics. Moreover, analyzing such a kind of data can facilitate deep understanding of individual life. In this study, we focus on personal data analytics to support well-being oriented life. Three categories of personal data are classified from the collection of individuals’ daily life data, and a framework of well-being oriented personal data analysis is proposed, which can provide people with suggestions and advices to improve their living life.

KW - Big data analysis

KW - Personal data

KW - Well-Being oriented life support

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A framework of personal data analytics for well-being oriented life support

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Keywords

ASJC Scopus subject areas

Access to Document

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