Because of advances in inertial microelectronics and
mobile computing technologies, highly accurate sensor hardware
has become ubiquitous in modern smartphones. This paper
introduces a framework that networks smartphone devices to
produce body sensor networks for motion capture and activity
tracking application areas. Data is transferred in real-time
using the motion cloud, an online gateway and storehouse for
inertial data. The goal of this research is to present a modular
methodology for amalgamating smartphone sensor data within a
centralized repository that is suitable for experimental research.
The proposed framework explores solutions for sensor fusion,
data synchronization, data streaming and remote control func-
tionality in smartphones. To demonstrate sensing accuracy, three
devices are strapped to the motion performer’s arm to record
the articulated motion of a hand wave gesture. To demonstrate
continuous sensing, two devices are networked for a period of
two hours to identify differences between sedentary and active
comportments.