Projekt REIF: Resource-efficient, Economic and Intelligent Foodchain

The ARXUM® project REIF is among the winners of the AI innovation competition of the BMWi

In Berlin, Dr. Ulrich Nussbaum, State Secretary in the Federal Ministry of Economics and Energy (BMWi), awarded the winners of the innovation competition "Artificial Intelligence as a Driver for Economically Relevant Ecosystems". The ARXUM® project REIF could become generally accepted and starts now into a three-year conversion phase promoted by the BMWi.

In the research project REIF the Potenziale of the artificial intelligence for the optimization of the plan and controllability of the creation of value in the foodstuffs industry is examined. Similar to machine learning, findings are continuously generated, multiplied and processes are optimized with this knowledge base. The goal of the project is to build up an AI ecosystem that integrates stakeholders of all stages of the value chain in such a way that food waste can be reduced sustainably and holistically with the help of Artificial Intelligence.
br />ARXUM® provides and develops the block chain infrastructure and smart contracts for the execution of the various use cases within the REIF AI ecosystem.

Key data REIF

  • Lifetime: 03/2020 - 02/2023
  • <Project partners: 18 partners from research and industry Federal Ministry of Economics and Energy (BMWi)

    Project website REIF

    Artificial intelligence against food waste

    The research project REIF - Resource-efficient, Economic and Intelligent Foodchain investigates the potential of AI artificial intelligence (AI) for optimizing the planning and control of value creation in the food industry. The goal of this research project is to establish a AI ecosystem that integrates stakeholders from all stages of the value chain in such a way that food waste can be reduced sustainably and holistically with the help of Artificial Intelligence.

    Food

    Starting point

    In Germany, several million tons of food are destroyed every year because they are no longer suitable for consumption for various reasons.studies show that 60%, i.e. approx. 11 million tons, is destroyed during the production process in the value chain.

    The complexity of the food industry - strict requirements for product safety, low planning in agriculture, countless product-specific boundary conditions in food processing, strong fluctuations in demand and the trend towards individualized products, also in the food industry, has so far prevented a reduction of these obvious deficits.

    Objective of the project

    The overall goal is the identification of potentials and the conceptualization of innovative approaches based on AI for learning value networks. For this purpose, REIF's approach is to design a value-added network for the food industry and use it as an AI ecosystem. This combined approach will create numerous synergies, so that the research area of AI, the food industry and society will benefit. Due to the strict legal regulations, the food industry generates an above-average amount of data, which is the nutrient of any AI approach. At the same time, the food chain's value creation has reached a temporary saturation point that can only be overcome by disruptive approaches such as the use of artificial intelligence. Therefore, the approach of this project focuses on the active use of AI processes by participating partners in the implementation phase. Analogous to machine learning, this application continuously generates and multiplies knowledge and optimizes processes with this knowledge base. To plan and prepare a structure and a network for this approach should be a crucial part of the competitive phase.

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