Where's The Bear (WTB)?

Automating Wildlife Image Processing Using IoT
and Edge Cloud Systems

Project Overview

WTB is a research project that investigates the design and implementation of an end-to-end, distributed, Internet of Things (IoT) system for wildlife monitoring. WTB

  • Is a multi-tier (public/private cloud, edge, sensing) system that integrates recent advances in machine learning based image processing to automatically classify animals in images from remote, motion-detection camera traps.
  • Uses non-local, resource-rich, public/private cloud systems to train machine learning models, and ``in-the-field,'' resource-constrained edge systems to perform classification near the IoT sensing devices (cameras).
  • Trains models using only empty images synthesized with randomly placed animal images from Google Images.
  • Relieves scientists and citizen scientists of the burden of manual image classification and saves time and bandwidth for image transfer off-site by automatically filtering the images on-site based on characteristics of interest.
  • Is deployed at the UCSB Sedgwick Reserve, a 6000 acre site for environmental research and used to aggregate, manage, and analyze over 1.12M images.

Team

  • PIs: Chandra Krintz and Rich Wolski
  • Collaborators:
    • Kate McCurdy (Sedgwick Reserve)
    • Grant Canova-Parker
  • Students:
    • Andy Rosales Elias
    • Nevena Golubovic

Support

  • NSF ACI-1541215 (Aristotle)
  • NSF CCF-1539586 (SmartFarm)

Publications and Presentations