Respiratory diseases are one of the main causes of death in the world, being among the global priorities proposed by the World Health Organization (WHO). Pulmonary auscultation is the main method of physical examination of the thorax that leads to a more accurate analysis of pulmonary function to detect respiratory diseases. This procedure is used by its functionality, as it is a non-invasive procedure and also because of the fast detection of abnormalities. Due to Coronavirus Disease (COVID-19), this technique has become essential to determine the severity of the disease, as it makes it possible to identify respiratory changes such as snoring and others problems. Therefore, this work presents a project space exploration to a system capable of performing automatic pulmonary auscultation, through a device capable of capturing the frequency of lung sounds. Many sensor nodes were implemented to evaluate the best solution to fit the auscultation problem. This system uses integration between hardware and software, using a microphone sensor node and a microcontroller board to process the data. The initial experiments performed demonstrated good results and high applicability for the auscultation problem.