An IoT and analytics platform for characterizing adolescent dogs' suitability for guide work

Zach Cleghern, Evan Williams, Sean Mealin, Marc Foster, Timothy Holder, Alper Bozkurt, David L. Roberts

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations


Evaluating potential guide dogs is crucial for guide dog schools as raising and training is an expensive process. During adolescence, volunteers raise dogs in training away from guide dog schools and expose them to a variety of stimuli and teach them obedience skills. However, no objective data exists about the dog's behavior and environment during this period, usually lasting several months to a year. We developed an Internet of Things sensor-equipped collar to quantify dogs' behaviors and environments during this stage. Raisers collect data from the collar using a smartphone app which in turn uploads data to a central processing pipeline. We present an overview of the system and an evaluation showing how we can learn meaningful information about a dog's environment and physical activities while away from the school for months on end, ideally to help predict which dogs will be successful in training.
Original languageEnglish (US)
Title of host publicationProceedings of the Sixth International Conference on Animal-Computer Interaction
ISBN (Print)9781450376938
StatePublished - Jan 10 2020
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-30
Acknowledgements: This material is based upon work supported by the NSF under Grant No. 1329738, 1554367, and 1160483. This work was also supported in part by a faculty award from IBM and a grant by KAUST. The authors would also like to enthusiastically thank Guiding Eyes for the Blind for their support.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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