Smart digital farming
- 1. Unlocking the potential of digitisation in Farming
- 2. Yes, there is a huge challenge! Precision Farming can do this Source:WorldResourcesInstitute
- 4. Industrie 4.0 Collective term for technologies and concepts for the organization and control of the entire value based primarily on cyber-physical systems, Internet of Things and Internet of Services
- 5. Cyber-fysic system? • Integration of the virtual and physical worlds • Intelligence, control and communication elements built into physical systems work together to monitor, control and integrate these systems. • Complex combination of large numbers of sensors and actuators are intelligent machines, with high autonomy, intelligence and connectivity through the integration of low- cost technology such as sensors, ICT applications, open source controller platforms
- 6. What is IOT? Porter and Heppelmann, Harvard Business Review, 2014 Now IT is embedded in products themselves creating smart connected objects
- 7. What is IOT? • combination of sensors and tiny devices embedded in physical objects and linked through wired and wireless networks that generate huge data volumes analysed in dedicated applications. M. Chui, M. Löffler, and R. Roberts. 'The Internet of Things'. McKinsey Quarterly, 2010.
- 8. • Static production • Difficult to reconfigure Example?
- 9. • Dynamic production • Autonomic movement between workstations • Individual variations
- 10. FARMING 4.0 = Smart Digital Farming Precision farming + Digitalisation
- 11. Combined with • Apps stores & cloud services (ICT-trends): – The internet is everywhere Bron: Kempenaar C. • Social media: direct and immediate contact between stakeholders Bron: AgJunction
- 12. In future • Data stream> • Money & Materials Need for a new internet: Internet of Things
- 13. Smart Digital Farming • = ranked as the technological opportunity with the highest expected positive impact on society Global Opportunity Report (2016)
- 14. Does the future look bright?
- 15. • Digital progress • Adoption • Penetration • Digital capacity =>lower than expected e.g. 35% smart spreaders
- 16. Try to identify the main reasons behind the current lack of adoption, and identifying the key barriers to the implementation of Precision Farming on European farms.
- 17. Need for smart digital ecosystems • Large potential in agriculture • Ecosystem of suppliers and stakeholders is very complex: – Large machine constructors – Suppliers van M2M technology and “decision support systems” – Advisory services, experts, service providers … – … • Large companies are digitalized via ERP (Enterprise Resource Planning) software but between smaller organizations there is a need for data exchange Bron: Kempenaar C.
- 18. • Via Cloud: the “connected farm” becomes reality – Real-time processen monitoring – Integrating • Weather data, climate, economy … • Product information and machine-settings – No installations or back-ups – Syncing mobile devices – Integration of business partners in the supply chain – Monitoring of several sites/locations Bron: Kempenaar C. Need smart digital ecosystem
- 21. • Robotica, automatisation and GNSS-technology • Connectivity (Internet of Things = IoT) • Big data analytics Explosion of data Data revolution in the Agri food sector • Strategy? Unlocking economic potential for Flanders of the data revolution in the Agro-food sector Digital Farming
- 22. Smart Digital Farming The specific objectives: -Increasing knowledge and expertise -Stimulating open and data-driven innovation -Establish concrete validation processes -Implementing new business models -Encouraging market-and product differentiation -Increasing the international visibility Netwerk Manager: Peter.rakers@ilvo.vlaanderen.be peterrakers@smartdigitalfarming.be Timing 3 years: 2017 -> 2019
- 23. IBN - Smart Digital Farming (1) Geo-ICT-companies: (2) Developers of sensors, drones and embedded controllers (3) Data-analytics (4) IOT –companies (5) Machine and barn equipment manufacturer 26 companies over the whole supply chain + observers SMART DIGITAL ecosystem (SDEs) in Agriculture = new interdisciplinary ecosystem to generate ‘data driven business models’
- 24. More Concrete …
- 25. Developers of sensors, drones and embedded controllers Geo-ICT- companies Machine /barn equipment manufacturersIOT – companies Data- analytics Networkwide activities DEFININING CASES (validatie tracks) SUCCES Designing a common validation path Support for further validation YES No BRAINSTORM SESSIONS
- 26. Network-wide activities Market research Cost-benefit/ estimating market potential Legislation– policy - standards Training/Education Identifying and promoting interesting calls Enlarging the network Internationalization Supporting demand driven research (S.R.A) Promoting Smart Farming
- 27. SUCCES Designing a common validation path Support for further validation Y N Lessons learnt cross-sectorial teams Market research Cost-benefit/ estimating market potential Proof of concept Feasibility tests Demonstration Legislation– policy - standards Facilitating knowledge exchange DEFININING CASES (validatie tracks
- 29. Dank Institute for Agricultural and Fisheries Research Technology and Food Science Unit 'Agricultural Engineering' and 'Product Quality and Innovation’ Research Areas Burg. Van Gansberghelaan 115 box 1 9820 Merelbeke T +32 9 272 28 00 www.ilvo.vlaanderen.be