Probabilistic Event EXtractor for RFID Data
---PEEX

Radio-Frequency Identification (RFID) technology is increasingly being used to support various industrial and ubiquitous computing applications. Although this technology holds the promise to facilitate many of our every day activities, the noisy and low-level data produced by RFID readers today is extremely difficult to use or comprehend in most but the simplest settings.

PEEX is a system that enables applications to easily define, extract, and manage meaningful probabilistic high-level events from low-level RFID data. By using a declarative query language, the system simplifies definitions of new events. By using probabilities, the system copes with the noise and errors in the data and the inherent ambiguity in the event extraction.

We have designed PEEX as a layer on top of a traditional RDBMS (currently Microsoft SQL Server). This design enables us to demonstrate the benefits of a probabilistic RFID DBMS, while leveraging all the features of an existing RDBMS. As illustrated in the figure below, the core components of PEEX are

1. Event Detector (extracts events specified by the event definitions)
2. Confidence Learner (learns from training data the historical probability that different combinations of tag sightings correspond to a high-level event)
3. Partial Event Generator (generates multiple partial events from one definition thus helping in coping with false negatives in the input data.)

Project Members

Students

• Nodira Khoussainova, University of Washington
• Julie Letchner, University of Washington
• Chris Re, University of Washington
• Evan Welbourne, University of Washington

Faculty

• Magdalena Balazinska, University of Washington
• Gaetano Borriello, University of Washington
• Dan Suciu, University of Washington

Publications

1. Evan Welbourne, Garret Cole, Nodira Khoussainova, Julie Letchner, Yang Li, Magdalena Balazinska, Gaetano Borriello, Dan Suciu. Specification, Detection, and Notification of RFID Events with Cascadia. MobiSys Demo 2008.
2. Evan Welbourne, Nodira Khoussainova, Julie Letchner, Yang Li, Magdalena Balazinska, Gaetano Borriello, Dan Suciu. Cascadia: A System for Specifying, Detecting, and Managing RFID Events. MobiSys 2008.
3. Nodira Khoussainova, Evan Welbourne, Magdalena Balazinska, Gaetano Borriello, Julie Letchner, Christopher Re, Dan Suciu, Jordan Walke. A Demonstration of Cascadia Through a Digital Diary Application. SIGMOD Demo 2008.
4. Nodira Khoussainova, Magdalena Balazinska, Dan Suciu. PEEX: Extracting Probabilistic Events from RFID Data. ICDE 2008. [Full version]
5. Nodira Khoussainova, Magdalena Balazinska, Dan Suciu. Probabilistic RFID Data Management. UW CSE Technical Report UW-CSE-07-03-01. March 1, 2007.

Acknowledgments

Last Modified at 2008-09-07 11:02:21 Pacific Daylight Time