FRED
Freshness data management from farm to fork in the edge
| Short description |
| FRED reduces the loss of fresh food along the supply chain, from producer to retailer to consumer, by integrating innovative measurement technology, digital twins for fruit and vegetable products, and a data space for freshness data within a trustworthy cloud-edge infrastructure. |
FRED uses the edge data economy to minimise waste and loss of perishable food along the supply chain, from producer to retailer to consumer. To this end, FRED is developing a freshness data management system that enables the detection and trustworthy exchange of data, particularly relating to fruit and vegetables. Innovative measurement techniques, predictions about the quality and freshness of food based on digital twins, and a data space for freshness data are integrated within an open infrastructure. The open data space enables different participants to share their data freely, in a manner that supports data sovereignty, and to use the data for further innovation and optimisation.
Market perspectives and product claims
Breakage and spoilage of fruit and vegetables cost the German food retail trade alone around €150 million every year. By implementing precise quality and shelf life assessments, FRED can reduce these losses by around 30%. FRED compiles data on food quality along the supply chain for this purpose and supplements it with hyperspectral image data captured when goods are received in wholesale or retail, along with publicly available data such as weather data.
FRED is developing several services and products to test the application of freshness data management: a device for non-destructive freshness determination in retail, digital twins of individual foods (e.g. the digital grape) and a framework for creating further digital twins, a platform for exchanging freshness data, and a consumer app that informs consumers about the shelf life of food and encourages them to use food sustainably. The sample implementation of freshness data management using individual food products in the project can also be transferred to other products. The results can be scaled up across Europe, helping to reduce food loss and waste throughout the region.
Challenge and innovation
FRED applies a holistic approach to address technical and socio-technical challenges facing the implementation of freshness data management in the food sector. Thanks to the project’s comprehensive scope, FRED’s freshness data management also offers solutions along the entire value chain from the producer (packer) to the consumer.
The technical challenges of the project include the trustworthy collection of sensor data and the execution of digital twins in real time on the edge devices. To this end, FRED is developing solutions for modelling and setting up complex, dynamic digital twins, combined with sovereign data exchange between different partners along the food supply chain. Simple development and use of digital twins is enabled via an edge-oriented platform established within the project and available along the entire food supply chain.
Use cases
The system developed in the project will be tested by way of example for certain fresh products (such as grapes) along the supply chain under varying practical conditions. Demonstrators are created for this purpose, both for incoming and outgoing goods. In this way, the shelf life forecasts created using digital twins can be verified, for example by checking the incoming quality after transportation or the outgoing quality at the point of goods issue. Laboratory tests and real-life applications provide proof of the practical suitability of the system and the data collected. The quality data and shelf life information are then also shared with consumers.
Consortium
Tsenso GmbH (consortium leader), Lippert Inspection GmbH, University of Freiburg, Osnabrück University
Benefits
| Current situation | Future vision |
| In the food trade, perishable food is mainly sorted using manual inspection and based on a forecast of the remaining shelf life, determined by the period since harvest. A lot of food that is still fit for consumption and sale thus ends up in the bin due to incorrect forecasts. | FRED offers users the option of predicting the remaining shelf life with high accuracy, using sources such as hyperspectral image data, publicly accessible data (e.g. weather data), and other quality data throughout the entire supply chain from production to sale. This helps to avoid a significant portion of today's food waste. |
| Data on the quality and ripeness of food is often inconsistently collected along the supply chain or may not be available to all stakeholders. | FRED is developing an end-to-end testing system for assessing the quality and ripeness of highly perishable foods, ensuring trustworthy and sovereign data exchange throughout the entire supply chain. |
| The exchange of freshness data does not take place via a central location. | FRED is developing a platform for exchanging freshness data. |
| No predictions about the freshness and quality of food. | Illustrative development of individual digital twins, based on the data collected for freshness management. |
| No end-to-end freshness data management available. | FRED has created an end-to-end ecosystem for freshness data management. Freshness data management facilitates the detection and trustworthy exchange of data on perishable foods, such as fruit and vegetables, in the interests of preventing food waste. |
