Intelligent waste & loss monitoring test bed for the Fish Can industry
Food loss and waste (FLW) in the fish processing chain is a particularly severe problem with approximately 35% of the input raw material being lost. Given the volumes of production and the size of the market it is clear the strong impact of FLW on the efficiency and sustainability of this particular food value chain in a context of continuously growing demand.
The source of such losses is manifold and hard to address not only because of the cultural resistance of a traditional sector such as that one of the fish industries but, most importantly, because of the large diversity of the variables involved and their complex interconnections.
This is particularly true for the fish canning industry where, nowadays, most of the processing steps are performed manually. Moreover, the perception of the potential of new technologies based on data, AI and others is not very spread among those industries, missing a great opportunity to apply those methods and making their processes more efficient.
iFishCan is a joint work proposed by a consortium of partners of three EIT Knowledge and Innovation Communities (EIT Manufacturing, EIT Food and EIT Digital) that will address this issue by designing, implementing, validating and demonstrating a low-cost, flexible, transportable and scalable smart FLW monitoring system for the fish manufacturing industry.
By applying machine learning techniques to food processing data and quality parameters as well as to environmental impact indicators the solution will generate prescriptive and predictive information about the most critical points of the chain in real time. This way, prompt corrective actions will be defined and implemented allowing to prevent or mitigate FLW and improve multiple environmental impact indicators (e.g., carbon and water footprint).
Expected outcomes and impact
- A solution that will substantially improve existing/traditional FLW systems by preventing the generation of FLW (instead of just monitoring it) and by mitigating the environmental impact of the fish processing chain, in line with the prescriptions of current circular economy policies.
- A testbed will be validated in two fish can factories (in Portugal and Spain), which will later allow escalating the initiative to other companies of the fish canning sector improving their sustainability and reducing their costs.
- The iFishCan system is expected to have a strong impact on multiple aspects of the production process of the fish companies adopting this solution: A 10% reduction of food loss during production; A reduction of 5-10% in energy consumption; A reduction of 5-20 % in water consumption will be pursued.
AZTI (leader) (EIT Food), AI Talentum (EIT Food), INESC TEC (EIT Manufacturing), FoodInTech (EIT digital)
EU – Horizon Europe