In Peru, the poultry industry is important due to the high consumption of poultry products by the population. However, there is an annual increase in bird mortality and morbidity rates on farms in the department of Junín. These birds suffer from various diseases that negatively impact the productivity and trade of the poultry sector, some of which are viral in origin and can be transmitted between humans and animals. It is crucial to implement thorough monitoring of bird growth and health to prevent bird mortality. This research aims to perform a proof of concept of a computer vision monitoring system for the detection of diseases in poultry farms in the Junín region. To this end, methods such as the black box were applied, which helped to identify the input and output signals of the monitoring system or equipment. Likewise, the morphological matrix was also made where the phases of operation and the respective alternatives were placed, this matrix helped to choose the best option for this project and follow a sequence for the best operation. In conclusion, it is expected that this project will contribute significantly to reducing poultry mortality on farms, thus preventing the frequent occurrence of different diseases among poultry populations.