Aprimoramento de sensor de ambiência para índices de conforto térmico em instalações de bovinos leiteiros

Abstract

Agribusiness is one of the most prominent economic activities in Brazil, and cattle farming is one of the most representative of them, but there is still a need for advances for it to remain competitive. The biggest stressor in dairy cattle farming is the climate, more specifically the heat, which affects considerably the welfare of the animals. In this context, the environment influences the living conditions of an organism, and the climate and the ability to adapt are responsible for influencing the behavior of the animals. In order to determine the effects of heat stress on animals, indices of thermal comfort have been developed taking into account climatic and/or physiological variables, helping producers and researchers to find the best means to reduce the stress caused by heat and determine the best time for measures to be implemented in order to provide thermal comfort to animals. Among the indices proposed in the literature, the temperature-humidity index (THI) and the black globe temperature and humidity index (BGTHI) stand out. Regarding rural workers, among the several existing thermal comfort indexes, we can highlight the thermal discomfort index (TDI). In order to obtain an ideal thermal environment for cattle in warm climatic regions, it is necessary to adequately monitor the environment to provide welfare to production animals and to achieve satisfactory zootechnical performance. In this sense, precision dairy farming, a management system based on information technology, enables greater control of animal and environmental variables, improving the performance of the dairy farm. To obtain values of climatic variables, there are devices known as dataloggers, which are nothing more than electronic devices that record data collected over a period of time, through sensors on its platform and that allow the calculation of thermal comfort indexes. In this work the objective was to improve a datalogger sensor capable of collecting biometeorological data from a dairy farm and transform them into ambience indices, providing the thermal classification of the environment to the producer. For this, a microcontrolled Arduino platform was used, with temperature and relative humidity sensors attached to it. The prototype read the climatic variables providing the values of air temperature, relative humidity, black globe temperature, dew point temperature, THI, BGTHI, TDI and thermal classification of the environment in favorable (comfort), alert (cold and heat) and danger (intense cold, intense heat and unbearable heat), thus responding to the producer's demand and consequently assisting in decision making regarding the appropriate management for the animal and rural worker welfare.