Resource-efficient computing in wearable systems

Mahsan Rofouei, Mahdi Pedram, Francesco Fraternali, Zhila Esna Ashari, Hassan Ghasemzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We propose two optimization techniques to minimize memory usage and computation while meeting system timing constraints for real-time classification in wearable systems. Our method derives a hierarchical classifier structure for Support Vector Machine (SVM) in order to reduce the amount of computations, based on the probability distribution of output classes occurrences. Also, we propose a memory optimization technique based on SVM parameters, which results in storing fewer support vectors and as a result requiring less memory. To demonstrate the efficiency of our proposed techniques, we performed an activity recognition experiment and were able to save up to 35% and 56% in memory storage when classifying 14 and 6 different activities, respectively. In addition, we demonstrated that there is a trade-off between accuracy of classification and memory savings, which can be controlled based on application requirements.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Smart Computing, SMARTCOMP 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages150-155
Number of pages6
ISBN (Electronic)9781728116891
DOIs
StatePublished - Jun 2019
Externally publishedYes
Event5th IEEE International Conference on Smart Computing, SMARTCOMP 2019 - Washington, United States
Duration: Jun 12 2019Jun 14 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Smart Computing, SMARTCOMP 2019

Conference

Conference5th IEEE International Conference on Smart Computing, SMARTCOMP 2019
Country/TerritoryUnited States
CityWashington
Period6/12/196/14/19

Keywords

  • Pervasive
  • Wearables

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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