The need to optimize and automate processes in the food industry is on the rise, and the pork industry is no exception. The value chain of this sector is highly complex due to the different actors involved: farms, transporters, slaughterhouses, cutting rooms, processors and distributors. For this reason, production control has to be exhaustive so as not to have errors at any point in the chain. The cutting rooms are in charge of the processes of getting the carcasses cut up and the products deposited in their respective compartments in just a few minutes, managing to maintain the cold chain and microbiological quality. In addition, the great heterogeneity of meat products makes control and traceability vital to offer a quality and safe product throughout the chain. The main objective of the DEPACA project is to research and develop a new solution that allows product classification in cutting rooms. The solution will allow optimizing the process and avoiding errors in the product. The project will investigate the identification of meat products in boxes in the cutting room using artificial vision and Deep Learning. As a result of the project, it is expected to achieve greater biogas production per ton of waste in the biogas plants, as well as to minimize the operating costs associated with waste management, improving the decarbonization potential of the renewable gas produced.
