Resource Efficient, Economic and Intelligent Foodchain

The Food industry is complex: product safety requirements are strict, forecasts for agricultural outcome are unreliable, and consumption trends can change quickly. Smart food chains, that reduce waste and help preserve the ecosystem, are needed more than ever. The REIF project, which stands for Resource-Efficient, Economic and Intelligent Food Chain, is looking to address this need through Artificial Intelligence (AI).

In the course of the next three years, the REIF project team will identify approaches and create concepts to reduce food waste based on AI. The large amount of data that the food industry has to generate to address strict regulatory demands is a great opportunity for an AI-based approach that uses such data to optimise processes in the food value chain.

The focus of REIF lies on three product groups – meat, dairy and bread – although a later inclusion of other product groups is planned. The research will look at both production streams (improving efficiency) and consumption streams (looking at better models to forecast demands). The aim is to create a better connection between consumption and production in support of food waste reduction.

The CSCP will facilitate the effective and efficient integration of all relevant stakeholders during and after the project. Another hallmark of CSCP’s engagement will be to support the development of an overarching platform for coordinated action among the project partners and beyond. Finally, the CSCP will apply its know-how on consumer behaviour and behaviour change in communication and consumer engagement activities related to dynamic pricing.

By analysing the needs of manufacturers, retailers and end consumers, the REIF project’s goal is to make AI-based services more effective and efficient, and thus increase their uptake from actors in the sector.

Watch this explainer video to learn how the REIF project places AI as an enabler for less waste and more sustainability in the food sector.


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The REIF consortium consists of 18 partners and it will be coordinated by the University of Applied Sciences Augsburg. The project is funded by the Federal Ministry of Economics and Energy (BMWi).