A mobile context monitoring platform for pervasive computing environments

In this paper, we present a new mobile platform to support emerging pervasive applications in a Personal Area Network (PAN)-scale dynamic mobile computing environment. The PAN-scale computing environment will constitute an important part of future pervasive-space technology with highly proactive applications, requiring continuous monitoring of users' contexts. The context-aware applications impose heavy workloads on the mobile device and the sensor nodes with highly limited computing and battery power especially for continuous monitoring of user contexts. Our new context monitoring system provides a scalable and energy-efficient monitoring architecture for such applications. It actively interplays between applications and computing resources, coordinating multiple applications to effectively leverage the limited resources and provide quality service to users. Example applications are also developed based on the implemented system design. Experimental results show that the system achieves a superior level of scalability and energy efficiency.

I. INTRODUCTION

Smart mobile devices have been the pivot for personal services. A large number of diverse sensors around the mobile device will enable highly proactive services with the help of a lot of personal context-aware applications, e.g., dietary monitoring [1], daily life assistant [5], sports training, interactive art [2], chronic disease monitoring, and elderly support, and health monitoring [3] [4], pervasive gaming [30] [31]. Situational appropriation of such services without user intervention requires an involved process for acquiring individuals' contexts. Individual users have different service requirements and preferences such as the system's level of proactive-ness and users’ privacy concerns. Applications require different types of contexts in different degrees of awareness. Future services will require much broader coverage and higher accuracy in recognized contexts.