Transforming
food risk
predictions
with
AI-Powered
Analytics

KNOW US BETTER

The first operational data and analytics platform dedicated to food safety risk prevention in Europe.

Mission

EFRA aspires to develop the first analytics-enabled, secure-by-design, green data space for AI-enabled food risk prevention. Our mission is to support EU’s global leadership in the digital-led industry transition from reaction to food risk prevention.

year program
European countries
Partners
real-world use cases

Real-time Editing

Implementation and rollout of new network infrastructure,including consolidation.

Interface Design

Implementation and rollout of new network infrastructure,including consolidation.

Creative Always

Implementation and rollout of new network infrastructure,including consolidation.

Real-time Editing

Implementation and rollout of new network infrastructure,including consolidation.

EFRA Project

Objectives

1 Solution development and testing, able to discover and distil meaningful and reliable food risk data from heterogeneous and dispersed data sources with minimal delay and appropriate format.

2 Designing of relevant human aspects and interactions with users to measure usefulness for human risk prevention actions in real-world scenarios and use-cases

3 Demonstrating how solutions enable the development of trustworthy, accurate, green and fair AI systems for food risk prevention

4 Groundbreaking advances in performance and usefulness of food risk data discovery, collection, mining, filtering, and processing

5 Integration of relevant technologies (such as big data, IoT, HPC, AI) to help achieve EFRA goals and foster links to respective communities of data innovators in the food supply chain

6 Positioning EFRA contributions into the overall ecosystem of public and private stakeholders that share data, technology and infrastructure to ensure the safety and quality of food in Europe

EFRA Project

Extreme Food Analytics Tools

DATA HUB

DATA HUB

A data platform able to search, mine, process, annotate, and link dispersed, heterogeneous, and deep/hidden food safety data sources.

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ANALYTICS POWERHOUSE

ANALYTICS POWERHOUSE

An analytics and AI platform with an extensible set of modules running over a green cloud High Performance Computing (HPC) able to distil useful insights & signals from the EFRA Data Hub, and train green AI models for food risk predictions.

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DATA & ANALYTICS MARKETPLACE

DATA & ANALYTICS MARKETPLACE

A front-facing user-friendly web app that allows interested users to discover, purchase/use, and contribute with raw data, AI models, and analytics modules, thus creating an economy where data holders and data consumers can engage and trade.

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EFRA PROJECT

Real-world Use Cases

USE CASE

Risk predictions for poultry pathogens

EFRA will monitor and predict the presence of the most usual pathogens in poultry farms. Lab test and environmental data coming directly from farm sensors, will be combined with publicly available data sources, related to poultry industry (such as incidents for products and inspection results). Leveraging these, this use-case will deploy and train appropriate AI models for poultry pathogen predictions.

egg-chicken-farm.jpg
egg-chicken-farm.jpg
AI models for
pathogen predictions
farmer-treats-the-field.jpg
farmer-treats-the-field.jpg
AI models for
optimal pesticide use
USE CASE

Enhanced Predictive Capabilities for Pest Alarms

Although the farm pesticides must satisfy specific EU requirements, farmers need assistance for the optimal (instead of maximum-allowed) use of pesticides, when it comes to food safety. In this use case the focus will be in 3 EU countries: Poland, Romania and Croatia. By leveraging both aggregated data from at-the-farm sensors and publicly available data sources, we will deploy and train AI models, for optimal pesticide use recommendations.

USE CASE

Informing Regulatory Decisions with Food Risk Intelligence

To identify potential emerging food safety risks, EFRA will use extensive set of regulatory data and mining algorithms, while different individuals, companies and organisations (such as food companies and food safety authorities) will upload relevant data using the EFRA tools. By using a unique approach all these heterogenous data sources will be combined, enhancing the introduction of food safety regulations, with significantly low computational and energy waste.

nutrition-facts.jpg
nutrition-facts.jpg
heterogenous data sources
will be combined
EFRA PROJECT

Expected Results

Transforming
food risk predictions
with
AI-Powered Analytics

We believe that our works can contribute to a better world.

01

Innovative extreme data mining and analysis methods and tools

02

Data analytics and AI Prediction Models

03

EFRA Green Data and Analytics Infrastructure

04

Open Food Intelligence Network for public and private stakeholders

05

Customised business models for each use case
our team

EFRA Partners

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