The WISDM (WIreless Sensor Data Mining) Project

Brief Project Overview

Mobile wireless devices, such as cell phones, PDA's, music players, notebook computers, are becoming increasingly powerful and sophisticated. Not only are their computing power and communication abilities expanding, but they now routinely incorporate a variety of sensors, including accelerometers, microphones, cameras, light sensors, and proximity sensors. Millions of people now carry these sensor-enabled mobile devices, which can either transmit the sensor data wirelessly to a server for remote processing or can process the data locally. This situation provides dramatic new opportunities for data mining and also makes it possible to deploy intelligent data mining applications on a scale not previously imaginable. This is where our WISDM (WIreless Sensor Data Mining) project comes in.

In this project we will collect and mine sensor data from these wireless devices. The scope of this project is enormous and there will be many opportunities for us to make an impact on how these smart mobile devices are used. Our initial focus was mainly on mining the accelerometer data, for tasks such as biometric identification and activity recognition (summarized below), but while we are continuing on in that area, we are now also actively looking into mining other sensor data, such as GPS data. Much of our focus right now, however, is in implementing the software architecture to transfer the sensor data from cellphones to our web-based server. Our initial platform will be based on the phones running Google's Android operating system (Nexus One, HTC Hero, Motorola Droid and Backflip, etc.). Our view is that these easy to program phones will eventually dominate the market.

Our preliminary work, which was based on a research oriented mobile device from Sun Microsystems, showed that we could accurately and reliably:

  • Identify a user or verify the identify of a user based on his/her accelerometer data (behavioral biometric identfication)
  • Identify the physical task that a user is performing (e.g., walking, jogging) based on the acceleromeer data (activity recognition)

Stay tuned for our exciting results! We expect to release some research papers that we are writing in the summer of 2010.

This project overlaps with a related project that is jointly being conducted with Dr. Warren Tryon from the Psychology department. While the WISDM project is quite general and spans all potential data mining applications of all forms of wireless sensor data, the project with Dr. Tryon focuses mainly on the accelerometer data and health care applications, leveraging Dr. Tryon's work on actigraphy.

Meeting Times

The WISDM research group meets most Thursdays from 6:30 - 8:30 at the Rose Hill campus of Fordham University, in JMH (John Mulcahy Hall) in the 4th floor Informatics and Data Mining lab. If you are are interested in joining the group, please contact Dr. Weiss.

Current Project Participants

Dr. Gary Weiss Computer and Information Science (project leader)
Active Participants
Anthony Alcaro Sophomore, FCRH, Computer & Information Science
Vincent Comer Senior, FCRH, Computer & Information Science
Anthony Gagliardo Junior, FCRH, Computer & Information Science
Shaun Gallagher Sophomore, FCRH, Computer & Information Science
Andrew Grosner Junior, FCRH, Computer & Information Science
Jeff Lockhart Sophomore, FCRH, Computer & Information Science
Paul McHugh Freshman, FCRH, Computer & Information Science
Sam Moore BS Graduate, FCRH, Computer & Information Science
Pierina Pino Junior, FCRH, Computer & Information Science
Tony Pulickal Sophomore, FCRH, Computer & Information Science
Gregory Rivas Sophomore, FCRH, Computer & Information Science
Vincent Sgro Senior, CBA, Business Administration
Phillip Walker Sophomore, FCRH, Computer & Information Science
Bethany Wolff Sophomore, FCRH, Computer & Information Science
Alvan Wong Senior, FCRH, Computer & Information Science
Zach Wyhowanec Sophomore, FCRH, Computer & Information Science
Jack XueMS student, GSAS, Computer & Information Science
WISDM Alumni (who made substantial contributions)
Jennifer Kwapisz Computer Science (BS), FCRH, 2010
Shane Skowron Computer Science (BS), FCLC, 2010
Affiliated Faculty
Dr. Warren Tryon Psychology Department