Energy efficient activity recognition based on low resolution accelerometer in smart phones

Yunji Liang; Xingshe Zhou; Zhiwen Yu; Bin Guo; Yue Yang

doi:10.1007/978-3-642-30767-6_11

Energy efficient activity recognition based on low resolution accelerometer in smart phones

Yunji Liang
, Xingshe Zhou
, Zhiwen Yu
, Bin Guo
, Yue Yang

School of Computer Science

Northwestern Polytechnical University Xian

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

23 Scopus citations

Abstract

Smart phone is becoming an ideal platform for continuous and transparent sensing with lots of built-in sensors. Activity recognition on smart phones is still a challenge due to the constraints of resources, such as battery lifetime, computational workload. Keeping in view the demand of low energy activity recognition for mobile devices, we propose an energy-efficient method to recognize user activities based on a single low resolution tri-axial accelerometer in smart phones. This paper presents a hierarchical recognition scheme with variable step size, which reduces the cost of time consuming frequency domain features for low energy consumption and adjusts the size of sliding window to improve the recognition accuracy. Experimental results demonstrate the effectiveness of the proposed algorithm with more than 85% recognition accuracy for 11 activities and 3.2 hours extended battery life for mobile phones.

Original language	English
Title of host publication	Advances in Grid and Pervasive Computing - 7th International Conference, GPC 2012, Proceedings
Pages	122-136
Number of pages	15
DOIs	https://doi.org/10.1007/978-3-642-30767-6_11
State	Published - 2012
Event	7th International Conference on Advances in Grid and Pervasive Computing, GPC 2012 - Hong Kong, China Duration: 11 May 2012 → 13 May 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7296 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Conference on Advances in Grid and Pervasive Computing, GPC 2012
Country/Territory	China
City	Hong Kong
Period	11/05/12 → 13/05/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

activity recognition
energy efficient
hierarchical recognition
low resolution
tri-axial accelerometer

Access to Document

10.1007/978-3-642-30767-6_11

Cite this

Liang, Y., Zhou, X., Yu, Z., Guo, B., & Yang, Y. (2012). Energy efficient activity recognition based on low resolution accelerometer in smart phones. In Advances in Grid and Pervasive Computing - 7th International Conference, GPC 2012, Proceedings (pp. 122-136). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7296 LNCS). https://doi.org/10.1007/978-3-642-30767-6_11

Liang, Yunji ; Zhou, Xingshe ; Yu, Zhiwen et al. / Energy efficient activity recognition based on low resolution accelerometer in smart phones. Advances in Grid and Pervasive Computing - 7th International Conference, GPC 2012, Proceedings. 2012. pp. 122-136 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Smart phone is becoming an ideal platform for continuous and transparent sensing with lots of built-in sensors. Activity recognition on smart phones is still a challenge due to the constraints of resources, such as battery lifetime, computational workload. Keeping in view the demand of low energy activity recognition for mobile devices, we propose an energy-efficient method to recognize user activities based on a single low resolution tri-axial accelerometer in smart phones. This paper presents a hierarchical recognition scheme with variable step size, which reduces the cost of time consuming frequency domain features for low energy consumption and adjusts the size of sliding window to improve the recognition accuracy. Experimental results demonstrate the effectiveness of the proposed algorithm with more than 85\% recognition accuracy for 11 activities and 3.2 hours extended battery life for mobile phones.",

keywords = "activity recognition, energy efficient, hierarchical recognition, low resolution, tri-axial accelerometer",

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}

Liang, Y, Zhou, X, Yu, Z, Guo, B & Yang, Y 2012, Energy efficient activity recognition based on low resolution accelerometer in smart phones. in Advances in Grid and Pervasive Computing - 7th International Conference, GPC 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7296 LNCS, pp. 122-136, 7th International Conference on Advances in Grid and Pervasive Computing, GPC 2012, Hong Kong, China, 11/05/12. https://doi.org/10.1007/978-3-642-30767-6_11

Energy efficient activity recognition based on low resolution accelerometer in smart phones. / Liang, Yunji; Zhou, Xingshe; Yu, Zhiwen et al.
Advances in Grid and Pervasive Computing - 7th International Conference, GPC 2012, Proceedings. 2012. p. 122-136 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7296 LNCS).

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

TY - GEN

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AU - Liang, Yunji

AU - Zhou, Xingshe

AU - Yu, Zhiwen

AU - Guo, Bin

AU - Yang, Yue

PY - 2012

Y1 - 2012

N2 - Smart phone is becoming an ideal platform for continuous and transparent sensing with lots of built-in sensors. Activity recognition on smart phones is still a challenge due to the constraints of resources, such as battery lifetime, computational workload. Keeping in view the demand of low energy activity recognition for mobile devices, we propose an energy-efficient method to recognize user activities based on a single low resolution tri-axial accelerometer in smart phones. This paper presents a hierarchical recognition scheme with variable step size, which reduces the cost of time consuming frequency domain features for low energy consumption and adjusts the size of sliding window to improve the recognition accuracy. Experimental results demonstrate the effectiveness of the proposed algorithm with more than 85% recognition accuracy for 11 activities and 3.2 hours extended battery life for mobile phones.

AB - Smart phone is becoming an ideal platform for continuous and transparent sensing with lots of built-in sensors. Activity recognition on smart phones is still a challenge due to the constraints of resources, such as battery lifetime, computational workload. Keeping in view the demand of low energy activity recognition for mobile devices, we propose an energy-efficient method to recognize user activities based on a single low resolution tri-axial accelerometer in smart phones. This paper presents a hierarchical recognition scheme with variable step size, which reduces the cost of time consuming frequency domain features for low energy consumption and adjusts the size of sliding window to improve the recognition accuracy. Experimental results demonstrate the effectiveness of the proposed algorithm with more than 85% recognition accuracy for 11 activities and 3.2 hours extended battery life for mobile phones.

KW - activity recognition

KW - energy efficient

KW - hierarchical recognition

KW - low resolution

KW - tri-axial accelerometer

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DO - 10.1007/978-3-642-30767-6_11

M3 - 会议稿件

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ER -

Liang Y, Zhou X, Yu Z, Guo B, Yang Y. Energy efficient activity recognition based on low resolution accelerometer in smart phones. In Advances in Grid and Pervasive Computing - 7th International Conference, GPC 2012, Proceedings. 2012. p. 122-136. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-30767-6_11

Energy efficient activity recognition based on low resolution accelerometer in smart phones

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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