Within the framework of the COGNOSFOOD project, supported by IVACE and FEDER funds, AINIA professionals are developing a platform that integrates various capabilities related to artificial intelligence models to automatically diagnose causes of quality problems in the plant (for example, non-homogeneous qualities, out-of-range batches, etc.) as well as anticipate or detect early quality or food safety problems (probability of contamination, etc.).

All of this is aimed at creating a safer industry with higher quality products, while simultaneously reducing the costs associated with these activities.

According to Juan Pablo Lázaro, from the information and communications technology department of AINIA: “This system will allow the integration of different predictive models, process simulations, developed with Deep learning technologies, and coordinate them from a global point of view, allowing intelligence to be at the service of the key processes of food product companies in a coordinated manner.”

The COGNOSFOOD project will develop a platform capable of hosting predictive and simulation models based on artificial intelligence that can be applied to quality control, food safety risk control, production efficiency and process control of the value chain, allowing the comprehensive use of data generated by food companies during the production process, with different integrated and coordinated applications.