"The routine daily
activities that tend to be sedentary and repetitive may cause severe health
problems. This issue has encouraged researchers to design a system to detect
and record people activities in real time and thus encourage them to do more
physical exercise. By utilizing sensors embedded in a smartphone, many research
studies have been conducted to try to recognize user activity. The most common
sensors used for this purpose are accelerometers and gyroscopes; however, we
found out that a gravity sensor has significant potential to be utilized as
well. In this paper, we propose a novel method to recognize activities using
the combination of an accelerometer and gravity sensor. We design a simple
hierarchical system with the purpose of developing a more energy efficient
application to be implemented in smartphones. We achieved an average of 95% for
the activity recognition accuracy, and we also succeed at proving that our work
is more energy efficient compared to other works."
