AI-driven collaborative supply and demand matching platform for food waste reduction in the perishable food supply chain

Project Details

Description

Goals: The overall goal of APPETITE is to reduce food waste by 10% by 2030 by means of prevention as described in the food waste hierarchy (Ciccullo et al. 2021). Moreover, logistics processes become more transparent and efficiency is increased by reducing handling and transportation costs. This is achieved by collaboration and the use of advanced data-driven technologies by integrating AI-driven forecasting and logistics optimization methods. Heterogeneous data integration and (near) real-time capabilities are the key innovations within APPETITE, which will enable a significant reduction of food waste in the future. Lack of collaboration and unused potential of heterogeneous data exploitation make an efficient matching of supply and demand impossible. A strong consortium is necessary, consisting of researchers and experts with domain-specific knowledge as well as three large European food retailers and an implementation partner with knowledge in the field of industrial AI applications. Together with LOI partners from the fields of food waste re-use, recycling, recovery, and disposal, APPETITE has the prerequisites to succeed in this challenging endeavor.
Results: The main result of APPETITE is a demonstrative prototype of a collaborative supply and demand matching platform for food retailers and wholesalers. A significant contribution to the efficient integration, analysis, and visualization of heterogeneous data in (near) real time is made. Sub-results generated are a heterogeneous data integration and analysis methodology, an AI-based forecasting platform, a (near) real-time monitoring and SC transparency dashboard, a food allocation concept considering the principles of the circular economy, and an overall scalable system architecture.

Financing body

Austrian Research Promotion Agency
StatusActive
Effective start/end date3/01/222/01/25

Collaborative partners

  • Vienna University of Economics and Business (lead)
  • Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. (Project partner)
  • Invenium Data Insight (Project partner)
  • IT-Power Services (Project partner)
  • Kastner Großhandelsgesellschaf (Project partner)
  • METRO Cash & Carry (Project partner)
  • SPAR Österreichische Warenhandels-Aktiengesellschaf (Project partner)
  • Vienna University of Technology (Project partner)

Austrian Classification of Fields of Science and Technology (OEFOS)

  • 502017 Logistics
  • 101015 Operations research
  • 211