Abstract
Radio frequency identification (RFID) holds the promise of real-time identifying, locating, tracking and monitoring physical objects without line of sight, and it can be used for a wide range of pervasive computing applications. To achieve these goals, RFID data have to be collected, transformed and expressively modeled as their virtual counterparts in the virtual world. RFID data, however, have their own unique characteristics–including aggregation, location, temporal and history oriented–which have to be fully considered and integrated into the data model. The diversity of RFID applications poses further challenges to a generalized framework for RFID data modeling. In this paper, we explore the fundamental characteristics of RFID applications, and classify applications into a set of basic scenarios based on these characteristics. We then develop constructs for modeling each scenario, which then can be integrated to model most complex RFID applications in the real world. We further demonstrate that our model provides powerful support on querying physical objects in RFID-based applications.
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