The relevance of creating a comprehensive system for meat control and identification to determine its freshness level has been demonstrated in the study. The drawbacks of traditional organoleptic and laboratory methods commonly used for meat inspection were analyzed. The authors presented the advantages and challenges of employing an electronic nose. A design for a meat control and identification system was proposed, which includes an Arduino Uno microcontroller, Raspberry Pi, USB to TTL adapter, gas sensors, color sensor, thermal camera, and image sensor. The proposed implementation of the electronic nose system on a single-board computer demonstrates its success in controlling and identifying meat freshness. A matrix of semiconductor gas sensors, TGS2602, MQ137, and MQ138, is formed as olfactory sensors, and TCS3200 is used as an RGB vision sensor, enabling the identification of the smell and color of different degrees of meat freshness. To obtain clear output differences from the gas sensors that react to the freshness level of meat, the baseline method is proposed for use. Therefore, a system enhanced with neural network capabilities will replace traditional devices for identifying meat freshness.
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