Beef cattle, as living, mobile organisms, one of the main livestock which produce the animal protein that is essential for humans, interact with their environment. The animal-environment system is very complex and digital data acquisition with IoT tools which create vast database open the way for producing valuable information for livestock practice. Precision livestock farming (PLF) technologies with application of machine learning and artificial intelligence methods are able to show hidden patterns and correlations between animal behavior and environment in real-time. These information supplement farmer’s knowledge about heat and health status of his livestock on pasture which influences his economic performance. It is important to highlight that the outdoor environment, which has a major impact on the performance of beef cattle, varies considerably from region to region. Given that pasture grass is the primary source of forage for beef cattle, its characteristics influence their movements and reproductive behavior. Our research investigates the mobility and estrus behavior of pasture grazed beef cattle using precision farming technology in a Hungarian context. Our research results have confirmed that the use of neck transponders can detect changes in cow activity and predict their heat instead of the farmer for the entire grazing period. By analyzing GPS data, we found that temperature influences the mobility of animals on pasture. The use of precision technologies in animal husbandry promotes prevention, efficiency, prediction of certain events, and lays the foundation for objective decision-making. Analysis of cattle behavior provides important findings for animal production practices, which can be incorporated into daily work processes with due consideration and competence.