NETE Caw’s Walking State Recognition Based on Accelerometers and Gyroscopes Installed on Ear- Tags and Collar-Tags.

Abstract

Caw’s walking detection is relevant, because the
quantity of times that a caw presents this state can be associated
with symptoms of estrus, lesions or even welfare degree. In order
to identify the characteristic movements associated with walking
actually it is common the use of inertial devices attached to the
animal's leg. The procedure of the device’s installation in the
animal’s leg entails risks to humans, animals and to the device.
This paper aims to clarify if the inertial sensors installed in the
animal's collar or even in an ear-tag can be used to estimate
patterns associated with the animal’s walking. Two devices with
IMU's (inertial measurement unit) were fabricated in order to
collect acceleration and gyroscope data from both, an ear-tag and
a collar-tag, installed simultaneously in a caw. The data used was
unfiltered and filtered with linear and angular Kalman filters,
then with each set of data, a support vector machines was trained.
The best result achieved was with the equal error rate (EER) of
17.5% for both cases (ear-tag and collar) with data filtered with a
linear Kalman filter. This error is similar to the error reached
with the device installed in the animal’s leg.