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Reconstructing Gene Networks of Forest Trees from Gene Expression Data: Toward Higher-Resolution Approaches Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Framework for Human Activity Recognition on Smartphones and Smartwatches

Authors : Blagoj Mitrevski, Viktor Petreski, Martin Gjoreski, Biljana Risteska Stojkoska

Published in: ICT Innovations 2018. Engineering and Life Sciences

Publisher: Springer International Publishing

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Abstract

As activity recognition becomes an integral part of many mobile applications, its requirement for lightweight and accurate techniques leads to development of new tools and algorithms. This paper has three main contributions: (1) to design an architecture for automatic data collection, thus reducing the time and cost and making the process of developing new activity recognition techniques convenient for software developers as well as for the end users; (2) to develop new algorithm for activity recognition based on Long Short Term Memory networks, which is able to learn features from raw accelerometer data, completely bypassing the process of generating hand-crafted features; and (3) to investigate which combinations of smartphone and smartwatch sensors gives the best results for the activity recognition problem, i.e. to analyze if the accuracy benefits of those combinations are greater than the additional costs for combining those sensors.

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Metadata
Title
Framework for Human Activity Recognition on Smartphones and Smartwatches
Authors
Blagoj Mitrevski
Viktor Petreski
Martin Gjoreski
Biljana Risteska Stojkoska
Copyright Year
2018
Book
ICT Innovations 2018. Engineering and Life Sciences

Print ISBN: 978-3-030-00824-6

Electronic ISBN: 978-3-030-00825-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-00825-3_8

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