Self M2M based wearable watch platform for collecting personal activity in real-time

Tracking and monitoring the history of personal activities by using wearable device can be applied in various different ways. For example, by analyzing the personal activities can be used to diagnose the symptoms of certain illness such as Parkinson's disease. The activity data can also tell the severity of the user's chronic illness. In this paper, we propose the watch platform which keeps the record of the user's activity data. This activity history is collected automatically inside the user's watch through peer-to-peer direct communicating with other devices. In order to implement self-awareness and the opportunistic computing manner in the watch platform, some advanced concepts such as ultra-low power consumption schemes and peer-to-peer direct communication between watch and external devices are included. On the proposed platform, we have implemented a prototype watch as a test bed for our software platform and also measured the several performance including power consumption rate and the computing opportunity of the prototype.