Food Sustainability insights for a healthy and climate neutral food chain

Partners: EV ILVO, GS1, Colruyt Group, Nijsen company, Palau BV

Objective: This use case aims to bolster the resilience and sustainability of the food supply chain, while also fostering the transition to healthier, sustainable eating habits. It achieves this by aggregating and analyzing accurate, primary agricultural data, as well as incorporating diverse, unconventional data types. These include data on physical fitness and sports activities, healthcare information, and the purchasing histories of medications and food additives in online pharma platforms.

Proposed solution: Collect and analyze a wide range of data, including agricultural, fitness, healthcare, and consumer purchase information. By enriching agricultural data with inputs from suppliers and feed supplement producers and merging this with data from online pharmacies and fitness trackers, the solution offers a holistic view of the supply chain. This comprehensive data set informs AI-driven tools that assist in making decisions about sustainable sourcing and processing methods, while also assessing the environmental impact of food products. Additionally, consumer-facing apps leverage this data to provide personalized dietary recommendations, aligning agricultural practices with consumer health and environmental sustainability. This strategy aims to promote informed choices towards healthier and more sustainable diets, improving food supply chain efficiency and resilience.

Areas of food Supply chain that will be affected:

Agricultural inputs production/Agricultural input suppliers: primary sustainability data from circular forage producers and aquaculture (seaweed).

Farming: agricultural production primary farm data sets to generate sustainability advice for farmers

Food processing: AI decision tool to support sustainable product sourcing and processing methods.
Consumer behaviour: A digital toolkit optimizing consumer app advice on food quality, product origins, health, and environmental impact, using data from various sources and personalized by location and language.

Share on:

More cases:

Use case 1
A DNA-data driven AI system for Food Sustainability and Traceability
Read More
Use case 2
Reimagining food services in hospitals and elderly care homes promoting health and sustainability
Read More
Use case 4
Enhancing Consumer Awareness of Sustainable Choices through High-Density Data-Driven Communication
Read More
A DNA-data driven AI system for Food Sustainability and Traceability
Read More
Reimagining food services in hospitals and elderly care homes promoting health and sustainability
Read More
Enhancing Consumer Awareness of Sustainable Choices through High-Density Data-Driven Communication
Read More