PetTrack

Neeraj Alavala, Haige Chen, Rishabh Singhal, Ashutosh Dhekne
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PetTrack
Tracking a pet’s location and activity indoors is of acute interest to pet owners who want to feel connected to their pet as well as of interest to pet owners who feel concerned about their pet’s well-being. Today, such tracking is performed using pet cameras. However, cameras need to be installed in every room accessible to the pet, do not work well in the dark, and generate a tremendous amount of data. In this paper we develop an indoor localization and pose detection system for pets using ultra-wideband (UWB) radios and an accelerometer affixed to the pet’s collar. We also develop a new message format for UWB packets to carry accelerometer data in addition to localization data to estimate the pet’s pose. Our pose-estimation logic detects the pet’s pose using accelerometer data via a K-nearest neighbor classifier. The pet’s location and pose is shown to the pet-owner via a functional mobile application. We believe this cost-effective and efficient new way of tracking a pet indoors will inspire others to extend this research further.
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