The study introduces a preliminary approach to enhance the supervision of food processing operators. Specifically, it showcases a digital model of an online compliance validation system with environmental conditions designed for food processing and preservation items that are sensitive to climate factors. The technology demonstration involves four fundamental stages carried out in a complete experimental cycle, where intelligent sensors gather and transmit data through a low-power wireless wide-area network from a farm specializing in sunflower seed storage. Subsequently, six consecutive scripts are executed, five of which are coded in Python. The integration of distributed data technology brings objectivity to the process of securely storing environmental parameters and objectively verifying their compliance with recommended hygienic, bio certification standards. As a result, monitoring the food production process becomes more publicly accessible and with higher rates of objectivity in decisions, enabling prospective buyers and certification agencies to assess the quality of food products with great precision. Therefore, the suggested digital model has the potential to ensure the utmost transparency in the food processing sector.
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