A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living

Giuseppe Amato; Davide Bacciu; Stefano Chessa; Mauro Dragone; Claudio Gallicchio; Claudio Gennaro; Hector Lozano; Alessio Micheli; Gregory M. P. O'Hare; Arantxa  Renteria; Claudio Vairo

doi:10.1007/978-3-319-40114-0_1

A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living

Giuseppe Amato, Davide Bacciu, Stefano Chessa, Mauro Dragone, Claudio Gallicchio, Claudio Gennaro, Hector Lozano, Alessio Micheli, Gregory M. P. O'Hare, Arantxa Renteria, Claudio Vairo

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

17 Citations (Scopus)

Abstract

We present a data benchmark for the assessment of human activityrecognition solutions, collected as part of the EU FP7 RUBICON project, andavailable to the scientific community. The dataset provides fully annotated datapertaining to numerous user activities and comprises synchronized data streamscollected from a highly sensor-rich home environment. A baseline activity recognition performance obtained through an Echo State Network approach is provided along with the dataset.

Original language	English
Title of host publication	Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016)
Editors	Helena Lindgren, Juan F. De Paz, Paulo Novais, Antonio Fernández-Caballero, Hyun Yoe, Andres Jiménez Ramírez, Gabriel Villarrubia
Publisher	Springer
Pages	1-9
Number of pages	9
ISBN (Electronic)	9783319401140
ISBN (Print)	9783319401133
DOIs	https://doi.org/10.1007/978-3-319-40114-0_1
Publication status	Published - 2016
Event	7th International Symposium on Ambient Intelligence 2016 - University of Sevilla, Sevilla, Spain Duration: 1 Jun 2016 → 3 Jun 2016 http://www.isami-conference.net/

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer International Publishing
Volume	476
ISSN (Print)	2194-5357

Conference

Conference	7th International Symposium on Ambient Intelligence 2016
Abbreviated title	ISAmI 2016
Country/Territory	Spain
City	Sevilla
Period	1/06/16 → 3/06/16
Internet address	http://www.isami-conference.net/

Keywords

Ambient assisted living
Human Activity Recognition
Datasets

ASJC Scopus subject areas

Artificial Intelligence
Signal Processing

Access to Document

10.1007/978-3-319-40114-0_1Licence: All Rights Reserved

Cite this

Amato, G., Bacciu, D., Chessa, S., Dragone, M., Gallicchio, C., Gennaro, C., Lozano, H., Micheli, A., O'Hare, G. M. P., Renteria, A., & Vairo, C. (2016). A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living. In H. Lindgren, J. F. De Paz, P. Novais, A. Fernández-Caballero, H. Yoe, A. J. Ramírez, & G. Villarrubia (Eds.), Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016) (pp. 1-9). (Advances in Intelligent Systems and Computing; Vol. 476). Springer. https://doi.org/10.1007/978-3-319-40114-0_1

Amato, Giuseppe ; Bacciu, Davide ; Chessa, Stefano et al. / A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living. Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016). editor / Helena Lindgren ; Juan F. De Paz ; Paulo Novais ; Antonio Fernández-Caballero ; Hyun Yoe ; Andres Jiménez Ramírez ; Gabriel Villarrubia. Springer, 2016. pp. 1-9 (Advances in Intelligent Systems and Computing).

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abstract = "We present a data benchmark for the assessment of human activityrecognition solutions, collected as part of the EU FP7 RUBICON project, andavailable to the scientific community. The dataset provides fully annotated datapertaining to numerous user activities and comprises synchronized data streamscollected from a highly sensor-rich home environment. A baseline activity recognition performance obtained through an Echo State Network approach is provided along with the dataset.",

keywords = "Ambient assisted living, Human Activity Recognition, Datasets",

author = "Giuseppe Amato and Davide Bacciu and Stefano Chessa and Mauro Dragone and Claudio Gallicchio and Claudio Gennaro and Hector Lozano and Alessio Micheli and O'Hare, {Gregory M. P.} and Arantxa Renteria and Claudio Vairo",

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booktitle = "Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016)",

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Amato, G, Bacciu, D, Chessa, S, Dragone, M, Gallicchio, C, Gennaro, C, Lozano, H, Micheli, A, O'Hare, GMP, Renteria, A & Vairo, C 2016, A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living. in H Lindgren, JF De Paz, P Novais, A Fernández-Caballero, H Yoe, AJ Ramírez & G Villarrubia (eds), Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016). Advances in Intelligent Systems and Computing, vol. 476, Springer, pp. 1-9, 7th International Symposium on Ambient Intelligence 2016, Sevilla, Spain, 1/06/16. https://doi.org/10.1007/978-3-319-40114-0_1

A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living. / Amato, Giuseppe; Bacciu, Davide; Chessa, Stefano et al.
Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016). ed. / Helena Lindgren; Juan F. De Paz; Paulo Novais; Antonio Fernández-Caballero; Hyun Yoe; Andres Jiménez Ramírez; Gabriel Villarrubia. Springer, 2016. p. 1-9 (Advances in Intelligent Systems and Computing; Vol. 476).

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

TY - CHAP

T1 - A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living

AU - Amato, Giuseppe

AU - Bacciu, Davide

AU - Chessa, Stefano

AU - Dragone, Mauro

AU - Gallicchio, Claudio

AU - Gennaro, Claudio

AU - Lozano, Hector

AU - Micheli, Alessio

AU - O'Hare, Gregory M. P.

AU - Renteria, Arantxa

AU - Vairo, Claudio

PY - 2016

Y1 - 2016

N2 - We present a data benchmark for the assessment of human activityrecognition solutions, collected as part of the EU FP7 RUBICON project, andavailable to the scientific community. The dataset provides fully annotated datapertaining to numerous user activities and comprises synchronized data streamscollected from a highly sensor-rich home environment. A baseline activity recognition performance obtained through an Echo State Network approach is provided along with the dataset.

AB - We present a data benchmark for the assessment of human activityrecognition solutions, collected as part of the EU FP7 RUBICON project, andavailable to the scientific community. The dataset provides fully annotated datapertaining to numerous user activities and comprises synchronized data streamscollected from a highly sensor-rich home environment. A baseline activity recognition performance obtained through an Echo State Network approach is provided along with the dataset.

KW - Ambient assisted living

KW - Human Activity Recognition

KW - Datasets

U2 - 10.1007/978-3-319-40114-0_1

DO - 10.1007/978-3-319-40114-0_1

M3 - Chapter

SN - 9783319401133

T3 - Advances in Intelligent Systems and Computing

SP - 1

EP - 9

BT - Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016)

A2 - Lindgren, Helena

A2 - De Paz, Juan F.

A2 - Novais, Paulo

A2 - Fernández-Caballero, Antonio

A2 - Yoe, Hyun

A2 - Ramírez, Andres Jiménez

A2 - Villarrubia, Gabriel

PB - Springer

T2 - 7th International Symposium on Ambient Intelligence 2016

Y2 - 1 June 2016 through 3 June 2016

ER -

Amato G, Bacciu D, Chessa S, Dragone M, Gallicchio C, Gennaro C et al. A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living. In Lindgren H, De Paz JF, Novais P, Fernández-Caballero A, Yoe H, Ramírez AJ, Villarrubia G, editors, Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016). Springer. 2016. p. 1-9. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-40114-0_1

A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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