4. Poor farmer – interoperability
needed
Farm management, the “rich picture” (Sörensen et al, 2010)
GI2012 – OpenDataPolicies 18.05.2012
5. What are current research focus and
what are main influence
• Currently research in developed World is mainly
focused on field level, eventually farm level
In practice, it could influenced farm profit
in range of 30 percent
• Possibilities to use macro level or external
information could influence farmers profitability in
hundreds percent
For example right selection of crops etc.
• So it is evident, that focus has to be in future on
work with external information
GI2012 – OpenDataPolicies 18.05.2012
7. Open Access to Information
• Will support decision farming processes
• Will help increase profitability of farm
• Will help with environment protection
• Will help to government better influence production
of food
• So PPP is necessary
GI2012 – OpenDataPolicies 18.05.2012
8. agriXchange challenges
• To include ICT and knowledge management for
agri-food and rural communities generally as a vital
part of the ICT policies and initiatives
• To find a balance between food safety and security,
energy production and environment production
• Support better transfer of RTD results and
innovation into everyday life of farmers, food
industry and other rural communities
GI2012 – OpenDataPolicies 18.05.2012
9. agriXchange challenges
• To accelerate bottom up activities as a driver for
local and regional development
• Making rural regions as an attractive place to live,
invest and work, promoting knowledge and
innovation for growth and creating more and better
jobs
• Build new ICT model for sharing and use of
knowledge in rural regions.
GI2012 – OpenDataPolicies 18.05.2012
10. ICT for Agriculture applications
vision
• Collaborative environments and trusted sharing of
knowledge and supporting innovations in agri-food
and rural areas, especially supporting food quality
and security
• ICT applications for the complete traceability of
production, products and services throughout a
networked value chain including logistics
• New generation of applications supporting better
and more effective management of agriculture
production and decision making in agriculture
• ICT applications supporting the management of
natural resources GI2012 – OpenDataPolicies 18.05.2012
11. ICT for Agriculture applications
vision
• ICT applications supporting agri-food logistic – the
focus has to be on the transportation and
distribution of food, sharing online monitoring
information from trucks during the transport of
cargo, a flexible solution for on-demand dock
reservation and an integrated freight and fleet
management. In general, all the selected
applications have the same practical benefits as
cost reduction, better coordination and better
information for decision making, and the proactive
control of processes leading to increasing
efficiency and effectiveness.
GI2012 – OpenDataPolicies 18.05.2012
12. ICT for Agriculture applications
vision
• ICT application supporting rural development and
local businesses
• ICT application for education and awareness
• ICT applications reducing administrative burdens in
rural areas
GI2012 – OpenDataPolicies 18.05.2012
13. ICT for Agriculture
Technological vision
• Future Internet and Internet of things including
sensor technology, cloud computing and machine
to machine.
• Service Oriented Architecture
• Methods of knowledge management
• Semantic models, multilingualism, vocabularies
and automatic translation
• Management and accessibility of geospatial
information
GI2012 – OpenDataPolicies 18.05.2012
14. ICT for Agriculture
Technological vision
• Open Source development
• New modeling
• The power of social networks and social media
GI2012 – OpenDataPolicies 18.05.2012
15. FI WARE and COIN vision
GI2012 – OpenDataPolicies 18.05.2012
18. Multiple criteria mathematical
programming using maxi-min principle
• In multiple criteria mathematical programming
problems, there is more than one objective
function. In case of our problem, individual
objective function will represent profits in different
scenarios.
• Solutions found by solving multiple criteria
mathematical programming are called compromise
solutions, because the most of the problems do not
have a solution providing the best values of all
objective functions at the same time.
GI2012 – OpenDataPolicies 18.05.2012
19. Multiple criteria mathematical
programming using maxi-min principle
• It the most of the methods, some additional
information including weights of each criteria is
required from decision maker.
GI2012 – OpenDataPolicies 18.05.2012