Open infrastructure for data sharing and interoperability between context-aware applications

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The recent proliferation of mobile and ubiquitous computing technologies (such as global positioning systems (GPS), radio frequency identification systems (RFID), and closed circuit television (CCTV)) has enabled the exploration of context-aware services which monitor and adapt to users, and provide them with useful services while they perform daily activities. The majority of existing research in context-aware computing has focused on three main areas: the construction of novel applications; the construction of new techniques and tools for sensing and inferring context and higher level activities; and the construction of software infrastructures to facilitate the development of this class of applications. Despite extensive investigations, research in this space has produced 1) a modest number of stand-alone applications which cannot interoperate with one another and 2) a set of techniques and tools for sensing and inferring context and high-level activities that are difficult to use interchangeably or evaluate comparatively. Investigators in each of these efforts have used homegrown representations of context information because no standards currently exist. We argue that these issues arise primarily because of the lack of a consistent information architecture used across the various context-aware applications and tools. To achieve interoperability and interchangeability requires that context data be sensed and shared in a meaningful way between different applications and tools. Furthermore, evaluation of the sensors, activity inferring techniques, and applications could be facilitated through the creation of common test data sets for comparing various tools. The proposed research involves the design, development, and evaluation of a flexible and open infrastructure for storing and accessing context information.