Project description
Innovative data-driven solutions for sustainable food chains
The agrifood industry faces public health, sustainability, waste, and data sharing challenges. Data can revolutionise the industry by helping the stakeholders make informed decisions, promoting sustainability and inclusivity, and thus optimising operations and reducing waste, and encouraging transparency and ethical production. The EU-funded FoodDataQuest project aims to develop innovative data-driven solutions to promote sustainable healthy diets for food chain stakeholders through a comprehensive framework that includes new data sources, unconventional players, and data sharing mechanisms. The framework comprises guidelines and data collection strategies to advance the food system towards healthy diets within legal and policy frameworks. The project uses AI and machine learning algorithms to create and test data-driven solutions for a fair, healthy and environmentally friendly food system, balancing data openness and privacy.
Objective
The agri-food industry faces numerous challenges dealing with societal, public health, individual nutrition and environmental, food waste and overall food system sustainability challenges. Imbalances and disconnected food markets are generating undesirable trade-offs between the food supply, the consumption patterns, quality of nutrition and the environment. Interoperability and data sharing across agri-food supply networks is limited. Data can revolutionise the food industry and foster its contribution to inclusive and sustainable food systems. Data can be used to assist these stakeholders in making informed decisions on how to operate in a more sustainable and inclusive manner. In this way, they increase the efficiency of the food industry through the optimisation of relevant operations and the reduction of waste, promoting transparency and demonstrate their commitment to ethical and sustainable production. FoodDataQuest will develop ground-breaking data-driven solutions based on an integrated methodological framework that explores new types of private and public data sources, data from “unconventional players” and non-competitive data and leverages data sharing mechanisms in order to provide the EU food chain stakeholders with increased insights and enhance the transition towards sustainable healthy diets. The proposed framework will include guidelines and data collection strategies, to drive the food system transformation towards inclusive, sustainable, healthy diets within the boundaries of legal and policy frameworks. FoodDataQuest will co-create and test advanced data-driven solutions based on AI and ML algorithms, following a multi-actor approach that will serve as a lighthouse that positively impacts a fair, healthy and environmentally friendly food system. Last, FoodDataQuest will engage citizens into industry's data-driven innovations balancing between data openness and protection of private and sensitive data of multiple stakeholders.
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Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
9820 Merelbeke
Belgium