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1
Sjaak Wolfert
Scientific Coordinator
Kick-off meeting, 6-7 Nov. 2018, The Hague, The
Netherlands
SmartAgriHubs:
objectives and
method
2 2
Table of
contents
1. Background and Context
2. SmartAgriHubs Objectives
3. Key Concepts
4. Project Approach
3
Big
Data
Analytics
Internet
of Things
Blockchain
Technology
Linked
Data
Cloud
Computing
Artificial
Intelligence
SENSING
& MONITORING
ANALYSIS
& PLANNING
SMART
SMART
SMART
PUBLIC DECISION-MAKING
food safety food security
healthenvironment
nutrition climate
CONTROL
FOOD
INTEGRITY
The Digital Transformation of Agri-Food
4
Overall objective
Consolidate and foster EU-wide network of Ag DIHs to enhance digital
transformation for sustainable farming and food production
5
Specific
Objectives
• Build network covering all EU
regions including technology,
business, sector expertise +
relevant players
• Critical mass of multi-actor
Innovation Experiments
• Financial support 3rd parties by
open calls – various public/private
funds
• Ensure long-term sustainability
incl. business plans + attracting
investors
5
6
Digital Innovation Hub
6
7
DIH Innovation Services
8
Concepts and coherence
• Layered network of Competence
Centers and Digital Innovation
Hubs organized in Regional
Clusters
• Multi-Actor Innovation
Experiments interacting with DIH’s
innovation services
• Innovation Services Maturity
Model developing the DIHs
• Innovation Portal supporting
Ecosystem Development
8
9
Approach
10
SAH Regional Clusters and WP structure
11

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Editor's Notes

  1. The management or decision support cycle increasingly becomes a cyber-physical cycle system monitored by advanced sensor networks and controlled by data and computer-based algorithms, tightly integrated with the internet and its users. In this way the cycle increasingly becomes autonomous, with less human intervention. This development can be applied to all parts of the food supply chain, while at the overall level data and high-tech are also driving new ways of traceability. But also public decision-making is increasingly supported by data-driven models and algorithms in order to make decisions on e.g. food safety or environmental control. Consequently, the data and related infrastructure for private and public purposes increasingly becomes intertwined in which the same data is used for multiple purposes, both private and public. However, this raises various issues on data ownership, -access, privacy, ethics etc. and progress will highly depend on creating trust and partnerships. Against this background we can distinguish four sub-themes that can be addressed by projects within these themes.