Energy and Accuracy Trade-Offs in Accelerometry-Based Activity Recognition


Wang, Ning, Merrett, Geoff V., Maunder, Robert G. and Rogers, Alex (2013) Energy and Accuracy Trade-Offs in Accelerometry-Based Activity Recognition At 2013 22nd International Conference on Computer Communications and Networks (ICCCN), Bahamas. 30 Jul - 02 Aug 2013. 6 pp, pp. 1-6. (doi:10.1109/ICCCN.2013.6614133).

Download

[img] PDF merrett.pdf - Accepted Manuscript
Download (750kB)

Description/Abstract

Driven by real-world applications such as fitness, wellbeing and healthcare, accelerometry-based activity recognition has been widely studied to provide context-awareness to future pervasive technologies. Accurate recognition and energy efficiency are key issues in enabling long-term and unobtrusive monitoring. While the majority of accelerometry-based activity recognition systems stream data to a central point for processing, some solutions process data locally on the sensor node to save energy. In this paper, we investigate the trade-offs between classification accuracy and energy efficiency by comparing on- and off-node schemes. An empirical energy model is presented and used to evaluate the energy efficiency of both systems, and a practical case study (monitoring the physical activities of office workers) is developed to evaluate the effect on classification accuracy. The results show a 40% energy saving can be obtained with a 13% reduction in classification accuracy, but this performance depends heavily on the wearer’s activity.

Item Type: Conference or Workshop Item (Paper)
Digital Object Identifier (DOI): doi:10.1109/ICCCN.2013.6614133
Additional Information: (c) IEEE 2013
Venue - Dates: 2013 22nd International Conference on Computer Communications and Networks (ICCCN), Bahamas, 2013-07-30 - 2013-08-02
Related URLs:
Keywords: activity recognition, body sensor networks, classification accuracy, energy efficiency
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Organisations: Agents, Interactions & Complexity, Electronic & Software Systems, Southampton Wireless Group
ePrint ID: 352018
Date :
Date Event
29 April 2013Accepted/In Press
July 2013Published
Date Deposited: 29 Apr 2013 10:41
Last Modified: 17 Apr 2017 15:35
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/352018

Actions (login required)

View Item View Item