Bridging physical and virtual worlds: complex event processing for RFID data streams

  • Authors:

  • Fusheng Wang;Shaorong Liu;Peiya Liu;Yijian Bai

  • Affiliations:

  • Integrated Data Systems Department, Siemens Corporate Research, Princeton, NJ;Computer Science Department, University of California, Los Angeles, Los Angeles, CA;Integrated Data Systems Department, Siemens Corporate Research, Princeton, NJ;Computer Science Department, University of California, Los Angeles, Los Angeles, CA

  • Venue:
  • EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
  • Year:
  • 2006

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Abstract

Advances of sensor and RFID technology provide significant new power for humans to sense, understand and manage the world. RFID provides fast data collection with precise identification of objects with unique IDs without line of sight, thus it can be used for identifying, locating, tracking and monitoring physical objects. Despite these benefits, RFID poses many challenges for data processing and management: i) RFID observations contain duplicates, which have to be filtered; ii) RFID observations have implicit meanings, which have to be transformed and aggregated into semantic data represented in their data models; and iii) RFID data are temporal, streaming, and in high volume, and have to be processed on the fly. Thus, a general RFID data processing framework is needed to automate the transformation of physical RFID observations into the virtual counterparts in the virtual world linked to business applications. In this paper, we take an event-oriented approach to process RFID data, by devising RFID application logic into complex events. We then formalize the specification and semantics of RFID events and rules. We demonstrate that traditional ECA event engine cannot be used to support highly temporally constrained RFID events, and develop an RFID event detection engine that can effectively process complex RFID events. The declarative event-based approach greatly simplifies the work of RFID data processing, and significantly reduces the cost of RFID data integration.