Sistema para aquisição e processamento de temperatura cutânea em bovinos e variáveis ambientais

Abstract

Thermal discomfort is one of the key factors that impact on the improvement of beef cattle production. Body temperature, air temperature and humidity, luminosity and Ultra Violet (UV) are some variables used to estimate the animal thermal comfort and the environment conditions thus helping to identify possible thermal stresses situations. The goal of this work is to automatize the acquisition of physiological and environmental variables to identify cattle thermal stress. The automation has been performed by the design, development, and prototyping of a computational/electronic system to acquire and process, at real time, physi-ological and environmental variables from cattle. The usage of the system indicates the cattle adaptability and behaviour under different climate conditions. The proposed system consists in an electronic platform with a set of sensors responsible for acquiring body temperature, environment temperature, luminosity, UV radiation, environment humidity, and algorithms responsible for controlling such sensors, data processing, storage, and communication. The environmental data are processed by a fuzzy algorithm designed to estimate shadow levels (sunny, natural shadow - trees, cloudy) in the cattle environment. We have carried out a set of experiments to validate and evaluate our system. Experiments on the shadow levels estimates have been performed onto 2 sets of data. The first one has collected environmental data using a commercial equipment along 8 consecutive hours in a day. Those data are converted and passed to our algorithm to estimate shadow levels. The second one has been performed using our own electronic system to acquire the environment data and identifying the shadow levels. Experiments considering the cattle body temperature have also been performed on 4 animals where we have observed the body temperature increase along a short period of time. The results on those experiments show the designed system is able to automatically acquire and process physiological and environmental data from a set of sensors.