PAWS: Precise Autonomous Wildlife Surveillance

Team Members:
Jason Dvorsky, EE '09
Kelvin Chan, EE '09
Taylor Caggiano, EE '09
Timothy Somerville, CSE '09

Team Faculty Advisor:
Professor Goeckel

Project Summary:

The Precise Autonomous Wildlife Surveillance (PAWS) system aims to improve methods of collecting information on animals in the wild. An autonomous system that will detect and predict motion in order to track a wildlife target, PAWS will improve on the quality of remote camera footage. While there exists remote camera sensing systems with stationary cameras, these systems can be very expensive when considering the number of cameras necessary to monitor wide fields of view. Being able to track with 360 degrees of lateral motion, PAWS will eliminate the need for multiple cameras, providing an enhanced viewing spectrum with only one camera. A prototype will be constructed to demonstrate the concept design with simple parameters (i.e. large target, simple background, limited tracking capabilities). A final model complete with zoom enhanced images and developed tracking methods shall be completed and simulated. This system intends to improve encounters of rare wildlife and shall produce longer, higher quality footage of rare species to be used in a multitude of contexts.

Click here for Final project report (May 2009)

Click here for Testing Plan documentation