Probabilistic Event EXtractor for RFID Data

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




  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.


The PEEX project is partially supported by NSF Grants IIS-0627585, IIS-0513877, IIS-0713576, CNS-0454425, CRI-0454394, the UW College of Engineering, and Gifts from Microsoft including a gift under the SensorMap RFP. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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