630 employees 320 scien<sts 200 ha fields > m² greenhouses > m² barns Food Pilot Factory etc.

Transcription

1 IOT DRIVEN FARMING

2 Plant Animal Social Technology & Food Flanders Belgium Wallonia 630 employees 320 scien<sts 200 ha fields > m² greenhouses > m² barns Food Pilot Factory etc. 2

3 Plant Sciences Agro Food Merelbeke/Melle Social Sciences Animal Sciences Technology and Food Science

4 ILVO is fully up to date New experimental greenhouse (2011) New pilot factory (2011) New dairy barn(2014) New pig research complex (2015)

5 Integrated research approach Soil à Fork Fork à Soil

6

7

8 Source Sanchez, J. VDI- Smart Farming

9 Source Sanchez, J. VDI- Smart Farming

10 A strong increase in produc<vity is necessary! Source Sanchez, J. VDI- Smart Farming

11 IOT = the 3rd wave? Porter and Heppelmann, Harvard Business Review, 2014 Now IT is embedded in products themselves creating smart connected objects

12

13 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.

14 Combined with Apps stores & cloud services (ICT-trends): The internet is everywhere Bron: AgJunc<on Social media: direct and immediate contact between stakeholders Bron: Kempenaar C.

15 In future Data stream> Money & Materials

16 How might we use IOT to further increase produc<vity?

17 Source Sanchez, J. VDI- Smart Farming Source Ian Morrison

18 Advancements in Farming 1.0 => 2.0 => 3.0 SMART SENSING & MONITORING BIG DATA SMART ANALYSIS & PLANNING SMART CONTROL Source Wolfert, S. IOF2020

19 Involving en<re supply chain and beyond Smart Farming Smart Logis<cs tracking & tracing Health Fitness/Well-being Source Wolfert, S. IOF2020

20 PigWise: monitoring fattening pigs RFID Feeding/drinking pattern individual pig Synergistic control ALARM for problems Differentiate abnormal and normal variation Online warning system for health, welfare and productivity problems

21 Animal Tracking AniAN X and Y coordinates, snapped at 0.1m No data loss during the experiment

22 So everybody is doing smart farming?

23 Yes except the farmers 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.

24 COST-BENEFIT COMPLEXITY: DATA INFORMATION DECISIONS? DATA OWNERSHIP, SECURITY, PRIVACY AND TRUST ISSUES

25 More and more connected things Source Sanchez, J. VDI- Smart Farming

26 Farming 3.5? Source Sanchez, J. VDI- Smart Farming

27 So we aren t there yet. Let s work on the way to 4.0?

28 So imagine that all objects on a farm and beyond could talk to each other? Source Sanchez, J. VDI- Smart Farming

29 TOWARDS TO A SMART FARMING (DATA) ECOSYSTEM FARMERS SCIENTIFIC COMMUNITY INVESTORS COOPERATIVES CONSORTIUM PARTNERS GENERAL PUBLIC AND MEDIA POLICY-MAKERS AND REGULATORS END-USERS Farm equipment suppliers Food processing companies Retailers Transporters Consumers associa<ons IOT TECHNOLOGY PROVIDERS AGRICULTURAL (INDEPENDENT) ADVISORY SERVICES NGOS & INTEREST ORGANISATIONS BUSINESS SUPPORT ORGANISATIONS Accelerators Incubators Chambers of commerce Enterprises networks hnps://iof2020.eu hnps:// Source Wolfert, S. IOF2020

30 SMART DIGITAL ECOSYSTEM FOR AGRICULTURE develop business cases of IoT in concrete applica<on areas Integrate and reuse available IoT technologies by exploi<ng open infrastructures and standards; Ensure user acceptability of IoT solu<ons by addressing user needs, including security, privacy and trust issues; (adop<on) large-scale uptake of IoT in the European farming and food sector 30

31 IOF2020 IN BRIEF 71 PARTNERS ORGANISATIONS 16 COUNTRIES 4 YEARS Start = January MILLION BUDGET ( 30 million co-funded under EU H2020 programme) 31

32 5 TRIALS, 19 USE CASES ARABLE FRUITS DAIRY VEGETABLES MEAT 32