Published January 21, 2020
| Version v1
Publication
A Sensor Fusion Horse Gait Classification by a Spiking Neural Network on SpiNNaker
Description
The study and monitoring of the behavior of wildlife has always been
a subject of great interest. Although many systems can track animal positions
using GPS systems, the behavior classification is not a common task. For this
work, a multi-sensory wearable device has been designed and implemented to be
used in the Doñana National Park in order to control and monitor wild and semiwild
life animals. The data obtained with these sensors is processed using a
Spiking Neural Network (SNN), with Address-Event-Representation (AER)
coding, and it is classified between some fixed activity behaviors. This works
presents the full infrastructure deployed in Doñana to collect the data, the wearable
device, the SNN implementation in SpiNNaker and the classification
results.
Abstract
Ministerio de Economía y Competitividad TEC2012-37868-C04-02Abstract
Junta de Andalucía P12-TIC-1300Additional details
Identifiers
- URL
- https://idus.us.es/handle//11441/91998
- URN
- urn:oai:idus.us.es:11441/91998