Temporal management of RFID data

RFID technology can be used to significantly improve the efficiency of business processes by providing the capability of automatic identification and data capture. This technology poses many new challenges on current data management systems. RFID data are time-dependent, dynamically changing, in large volumes, and carry implicit semantics. RFID data management systems need to effectively support such large scale temporal data created by RFID applications. These systems need to have an explicit temporal data model for RFID data to support tracking and monitoring queries. In addition, they need to have an automatic method to transform the primitive observations from RFID readers into derived data used in RFID-enabled applications. In this paper, we present an integrated RFID data management system - Siemens RFID Middleware - based on an expressive temporal data model for RFID data. Our system enables semantic RFID data filtering and automatic data transformation based on declarative rules, provides powerful query support of RFID object tracking and monitoring, and can be adapted to different RFID-enabled applications.