Pervasive and Mobile Computing 6 (2010) 382–397 Contents lists available at ScienceDirect Pervasive and Mobile Computing journal homepage: www.elsevier.com/locate/pmc Fast track article A temporal RFID data model for querying physical objects Fusheng Wang a,∗,1 , Shaorong Liu b , Peiya Liu c a Center for Comprehensive Informatics, Emory University, 1784 North Decatur Road, Atlanta, GA 30033, USA b IBM Silicon Valley Lab, San Jose, CA, USA c Integrated Data Systems Department, Siemens Corporate Research, 755 College Road East, Princeton, NJ 08540, USA article info Article history: Received 8 October 2008 Received in revised form 2 October 2009 Accepted 3 October 2009 Available online 7 October 2009 Keywords: RFID Data model Temporal data Location 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. © 2009 Elsevier B.V. All rights reserved. 1. Introduction Radio frequency identification (RFID) technology uses radio frequency waves to transfer data between readers and movable tagged objects. Thus it is possible to create a physically linked world in which every object can be numbered, identified, cataloged, and tracked. RFID is automatic and fast, and does not require line of sight or contact between readers and tagged objects. With such significant technology advantages, RFID has been gradually adopted and deployed in a wide area of applications, such as access control, library checkin and checkout, document tracking, smart box [1], highway tolls, supply chain and logistics, security, healthcare, etc. One major benefit in RFID-enabled applications is the ability to automatically identify, locate, track and monitor physical objects in real time. Physical objects can be uniquely identified by tagging them with RFID tags and virtually representing them as EPC — Electronic Product Code is an identification scheme for universally identifying physical objects, defined by EPCGlobal [2]. Readers can be deployed at different locations and networked together providing an RFID-based pervasive computing environment as illustrated in Fig. 1, where L1–L6 denote locations mounted with readers. Tagged objects moving in this environment will then be automatically sensed and observed with their identifications, locations and movement paths. The readers’ observations, however, are raw data and they provide no explicit semantic information on application or business logic. They have to be transformed into semantic data properly represented with their own data models before ∗ Corresponding author. E-mail addresses: fusheng.wang@emory.edu (F. Wang), shaorong.liu@gmail.com (S. Liu), peiya.liu@siemens.com (P. Liu). 1 Work done while working at Siemens Corporate Research. 1574-1192/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.pmcj.2009.10.001