This work  presents an animal behavior recognition, classification and monitoring system based on a wireless sensor network and a smart collar device, provided with inertial sensors and an embedded multi-layer perceptron-based feed-forward neural network, to classify the different gaits or behaviors based on the collected information.
The paper  considers the choice of a radio transceiver module for use in a wireless sensor network aimed at wildlife monitoring.
In this application, power consumption and communication range in difficult terrain are key challenges.
Authors of  deploy An MWSN for animal monitoring in the Amazon rainforest of Peru. Tapirduino, the developed trap camera sensor node, is composed by an Arduino-like PCB, a CMOS camera, an IR flash, a PIR sensor, a SD card, and 900-MHz radio. The challenges tackled in this project were to overcome the high attenuation of radio frequency in the middle of the jungle and to reduce energy consumption until achieving a very low level.