Activity recognition using smartphones and wearable devices: Traditional approaches, new solutions - Iskanderov, Jemshit; Guvensan, Mehmet Amac (PAMUKKALE UNIV, 2019)
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; MOBILE ACTIVITY RECOGNITION; CLASSIFIERS; SYSTEM; Engineering