Human activity recognition in big data smart home context

Sabrina Azzi; Abdenour Bouzouane; Sylvain Giroux; Cindy Dallaire; Bruno Bouchard

doi:10.1109/BigData.2014.7004406

Human activity recognition in big data smart home context

Sabrina Azzi
, Abdenour Bouzouane
, Sylvain Giroux
, Cindy Dallaire
, Bruno Bouchard

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

7 Citations (Scopus)

Abstract

In smart homes, a few millions of data are sent by different sensors and RFID per day. It thus constitutes a Big Data warehouse with all the problems that come from and in our work, we are interested in the problem of managing huge data in streaming. In this paper, we propose to use very fast decision tree(VFDT) for activity recognition. We formulate Activity Recognition as a classification problem where classes correspond to activities. The performance of the VFDT and other classifiers is compared.

Original language	English
Title of host publication	2014 IEEE International Conference on Big Data (Big Data)
Publisher	IEEE
Number of pages	8
ISBN (Print)	9781479956661
DOIs	https://doi.org/10.1109/BigData.2014.7004406
Publication status	Published - 8 Jan 2015
Externally published	Yes

Keywords

big data
smart home
data mining
activity recognition

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10.1109/BigData.2014.7004406

Cite this

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title = "Human activity recognition in big data smart home context",

abstract = "In smart homes, a few millions of data are sent by different sensors and RFID per day. It thus constitutes a Big Data warehouse with all the problems that come from and in our work, we are interested in the problem of managing huge data in streaming. In this paper, we propose to use very fast decision tree(VFDT) for activity recognition. We formulate Activity Recognition as a classification problem where classes correspond to activities. The performance of the VFDT and other classifiers is compared.",

keywords = "big data, smart home, data mining, activity recognition",

author = "Sabrina Azzi and Abdenour Bouzouane and Sylvain Giroux and Cindy Dallaire and Bruno Bouchard",

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AU - Azzi, Sabrina

AU - Bouzouane, Abdenour

AU - Giroux, Sylvain

AU - Dallaire, Cindy

AU - Bouchard, Bruno

PY - 2015/1/8

Y1 - 2015/1/8

N2 - In smart homes, a few millions of data are sent by different sensors and RFID per day. It thus constitutes a Big Data warehouse with all the problems that come from and in our work, we are interested in the problem of managing huge data in streaming. In this paper, we propose to use very fast decision tree(VFDT) for activity recognition. We formulate Activity Recognition as a classification problem where classes correspond to activities. The performance of the VFDT and other classifiers is compared.

AB - In smart homes, a few millions of data are sent by different sensors and RFID per day. It thus constitutes a Big Data warehouse with all the problems that come from and in our work, we are interested in the problem of managing huge data in streaming. In this paper, we propose to use very fast decision tree(VFDT) for activity recognition. We formulate Activity Recognition as a classification problem where classes correspond to activities. The performance of the VFDT and other classifiers is compared.

KW - big data

KW - smart home

KW - data mining

KW - activity recognition

U2 - 10.1109/BigData.2014.7004406

DO - 10.1109/BigData.2014.7004406

M3 - Conference contribution

SN - 9781479956661

BT - 2014 IEEE International Conference on Big Data (Big Data)

PB - IEEE

ER -

Human activity recognition in big data smart home context

Abstract

Keywords

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Cite this