Akıllı telefon ve giyilebilir cihazlarla aktivite tanıma: Klasik yaklaşımlar, yeni çözümler

Year 2019, Volume: 25 Issue: 2, 223 - 239, 22.04.2019

Jemshit Iskanderov Mehmet Amaç Güvensan

Abstract

Son
yıllarda özellikle akıllı telefonların ve giyilebilir cihazların gelişmesiyle
birlikte aktivite tanıma alanındaki çalışmalar hız kazanmıştır. Aktiviteler
temel olarak yürüme, koşma gibi basit aktiviteler ve yemek yeme, uyuma, diş
fırçalama gibi karışık aktiviteler olmak üzere ikiye ayrılmaktadır. Bu derleme
çalışmasında aktivite tanıma konusu ile ilgili makaleler değerlendirilmiş ve
aktivite tanımada kullanılan sensörler, aktivite çeşitleri, uygulama alanları,
aktivite tanıma için kullanılan cihazlar, veri toplama işlemi, eğitim
yöntemleri, sınıflandırma algoritmaları ve kaynak tüketimi konuları detaylı
olarak incelenmiştir. Yapılmış çalışmaların mevcut durumu ortaya konmuş ve
kullanılan farklı yöntemler karşılaştırılmıştır. Daha sonra açık veri setleri paylaşılmış
ve literatürdeki derin öğrenme yöntemleri kullanan yenilikçi çözümlerden
bahsedilmiştir. Son olarak, bu alanda hala açık olan noktalardan bahsedilmiş ve
ileride çalışma yapılabilecek konular önerilmiştir.

Keywords

Aktivite tanıma, Akıllı telefon, Giyilebilir cihaz, Derin öğrenme, Veri seti, Derleme

Activity recognition using smartphones and wearable devices: Traditional approaches, new solutions

Abstract

In
recent years, the research on activity recognition has gained speed especially
with the development of smart phones and wearable devices. Activities could be
categorized into two main groups. simple activities such as walking, running
and complex activities such as eating, sleeping, brushing teeth. In this survey
paper, articles about activity recognition are examined thoroughly. Sensors and
devices used in activity recognition, types of daily activities, application
areas, data collection process, training methods, classification algorithms and
resource consumption are mentioned in details. The state of the art is
elaborated and the existing methods are compared to each other. Later, open
data sets are mentioned and studies offering innovative solutions using latest
approaches such as deep learning methods are introduced. Finally, still open
issues on this area are presented and future work has been discussed.

Keywords

Activity recognition, Smartphone, Wearable device, Deep learning, Dataset, Survey

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