EIT

EIT iFishCan - Intelligent Waste & Loss Monitoring Test Bed for the Fish Can Industry

Background

Food loss and waste (FLW) in the fish processing supply chain is a particularly serious issue, with estimates suggesting that approximately 35% of the raw materials used are lost. Given the production volumes and market size, the significant impact of FLW on the efficiency and sustainability of this food value chain becomes clear, particularly in the context of continuously growing demand.

The causes of these losses are diverse and difficult to address, not only because of cultural resistance within a traditional sector such as the fish processing industry, but above all due to the wide range of variables involved and the complex relationships between them.

This situation is particularly evident in the fish canning industry, where a large proportion of processing stages are still carried out manually. Furthermore, awareness of the potential of emerging data-driven technologies, Artificial Intelligence and other digital solutions remains limited within these industries, resulting in missed opportunities to apply these methods and improve process efficiency.

Solution

iFishCan is a joint project proposed by a consortium of partners from three EIT Knowledge and Innovation Communities: EIT Manufacturing, EIT Food and EIT Digital.

The project aims to address this challenge through the design, implementation, validation and demonstration of an intelligent FLW monitoring system that is low-cost, flexible, portable and scalable, specifically developed for the fish processing industry.

By applying machine learning techniques to food processing data, quality parameters and environmental impact indicators, the solution will generate real-time predictive and prescriptive insights into the most critical points of the production chain.

This will enable corrective actions to be quickly identified and implemented, helping to prevent or reduce food loss and waste while improving various environmental impact indicators, such as carbon and water footprints.

Expected Results and Impact

The aim is to develop a solution that significantly improves traditional FLW management systems by preventing food loss and waste rather than merely monitoring them, while simultaneously reducing the environmental impact of the fish processing supply chain, in line with current circular economy policies.

A testbed will be validated in two fish canning factories located in Portugal and Spain. This initiative may subsequently be extended to other companies in the canning industry, contributing to greater sustainability and reduced operating costs.

The iFishCan system is expected to have a significant impact on several aspects of the production processes of companies adopting the solution, including:

• 10% reduction in food losses during production;
• 5% to 10% reduction in energy consumption;
• 5% to 20% reduction in water consumption.

Project Details

Partners | AZTI (lead partner) - EIT Food, AI Talentum - EIT Food / EIT Digital, INESC TEC - EIT Manufacturing, FoodInTech - EIT Digital

Funding | European Union - EIT

Duration | 2021