Presentation 2012-08-21
M2M Data Analysis Service System based on Open Source Software Environment
Shinji KITAGAMI, Moriki YAMAMOTO, Hisao KOIZUMI, Takuo SUGANUMA,
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Abstract(in English) In data analysis of M2M (Machine-to-Machine) service system, it is necessary to satisfy the three requirements of large amounts of data, real-time and deep analysis simultaneously. However, in general, in order to build systems that satisfy these requirements, it is necessary to the introduction of expensive software products such as DSMS (Data Stream Management System). In this paper, we propose a service system for data analysis applied to small-and medium-sized M2M service system, by utilizing open source software environment, such as the R and SQLite. In this study, based on the application scenarios that are intended to be applied to the demand response of the smart grid, we evaluated the effectiveness of the proposed system.
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Keyword(in English) Demand Response / Remote Maintenance / Stream Data Analysis / Accumulated Data Analysis / DSMS / SQLite / R
Paper # SWIM2012-13
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Committee SWIM
Conference Date 2012/8/14(1days)
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Registration To Software Interprise Modeling (SWIM)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) M2M Data Analysis Service System based on Open Source Software Environment
Sub Title (in English)
Keyword(1) Demand Response
Keyword(2) Remote Maintenance
Keyword(3) Stream Data Analysis
Keyword(4) Accumulated Data Analysis
Keyword(5) DSMS
Keyword(6) SQLite
Keyword(7) R
1st Author's Name Shinji KITAGAMI
1st Author's Affiliation Information Technology R&D Center, Mitsubishi Electric Corporation:Graduate School of Information Sciences, TOHOKU University()
2nd Author's Name Moriki YAMAMOTO
2nd Author's Affiliation Itec
3rd Author's Name Hisao KOIZUMI
3rd Author's Affiliation Tokyo Denki University
4th Author's Name Takuo SUGANUMA
4th Author's Affiliation Cyberscience Center, TOHOKU University:Graduate School of Information Sciences, TOHOKU University
Date 2012-08-21
Paper # SWIM2012-13
Volume (vol) vol.112
Number (no) 179
Page pp.pp.-
#Pages 6
Date of Issue