Uploaded byKim Escherich
Eat Data - How digitization is changing the food chain
The document discusses how digitization, including the use of IoT, AI, and big data, is transforming the food chain and agriculture systems. It emphasizes the importance of traceability, precision agriculture, and the role of emerging technologies in improving crop yields and resource management. Key principles for innovation in the food system include understanding value creation, involving all stakeholders, and prototyping solutions for long-term benefits.
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Eat Data - How digitization is changing the food chain
- 1. 1 How digitization ischanging the food chain Kim Escherich | Executive Innovation Architect | IBM | @kescherich
- 2. Kim Escherich Executive InnovationArchitect IBM • Internet of Things • Artificial intelligence • Smarter Cities • Traceability • Emerging technologies • Big data • Analytics • Supply chain • Food systems • Agriculture • Innovation • Food activism (Foodpeace.org) • Food startups • Food photographer @kescherich | @danmark50 /in/escherich www.internetofthings.dk Traceability and anti- counterfeitsolutions for the European flower industry Global postal monitoring using active RFID Traceability in supply chain processes in construction Blueprint for traceability in the Swedish fishing industry
- 3. The food system? Whatis it – seen from the consumer - and what is going on? 3
- 4. Do we know,what we don’t know? …and do we really want to know? Pink slime like substance to produce chicken sausages – just left the centrifugal separator
- 5. 5 And if…, howshould we do the right actions?
- 6. 6 Carlo Ratti Associati:Supermarketofthe future How to decide? I contain residues from 38 pesticides and other chemicals. Buy me, please! Please?
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- 8. And what aboutmy health? 60% 30% 10% Exogenous data 1,100Terabytes Generatedper lifetime 8 Genomics data 6 TB Per lifetime Influence on outcomes Clinical data 0.4 TB Per lifetime Source: "The Relative Contribution of Multiple Determinants to Health Outcomes", Lauren McGover et al., Health Affairs, 33, no.2 (2014)
- 9. HealthifyMe: Smart health& fitness assistant
- 10. So…, how todigitize this? Neds, opportunities and technologies to support? 10
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- 12. Key enablers for foodsystem innovation INTERNET OF THINGS BLOCKCHAIN BIG DATA ARTIFICIAL INTELLIGENCE
- 13. 13 AI is changingthe way we interact Source: Standard Cognition
- 14. Watson Visual Recognitionfor Food Largest known collection: > 1.5 million food images Food Score Strawberry dipped in chocolate Fruit dipped in chocolate 1.00 Fruit dish Sweet treat Chocolate egg Easter egg Candy Sweet Delicacy 1.00 1.00 1.00 .50 .50 .50 .50 .50
- 15. 15 Dear AI, Whatto eat tonight? https://www.ibmchefwatson.com
- 16. Bear Naked ® Firstconsumer brand to offer Chef Watson-inspired foods IBM Chef Watson Choose over 50 fresh ingredients Personalised Granola (available through subscription)
- 17. © 2016 IBMCorporation 17 Source: McKinsey: The Age of Analytics – Competing in a data-driven world http://www.mckinsey.com/business-functions/mckinsey-analytics/our-insigh ts/the-age-o f-analytics-competing-in-a-data-driven-world AI has great potential
- 18. Agriculture + IoT= really BIGdata Nitrogen Sensors GPS/GIS Data from Satellites Drone Sensor and Image Transmissions Weather Data Crop Modeling Environmental Data – temp, humidity, wind, heat units Soil Moisture Sensors Drip Irrigation Sensors Pivot Irrigation Sensors Social Media Yield Sensors on Harvesting Equipment Application Sensors for Inputs Seeding/ Planting Sensors Connected Tractors & Harvesters
- 19. 19 Precision Agriculture –Logical Architecture Farm/Field Insights Marketplace Mobile Equipment Weather Literature Drones Soil Yield Topography Data Ingestion and High Performance Computing Watson IoT Connect Massive Store SQL/No SQL Geo Spatial Weather Insights Decision AgricultureHub Soil Analytics Weather Analytics Agro Advisories Watson Alchemy TradeOff Analyzer Insights for Twitter Predictive Analytics Streaming Analytics Government/ Universities Precison Agri Business/Industrial Farms Cooperatives Channels Client Experience Forecasts Mobile Enabled Visualization Portals Ad-Hoc and Advanced Decision Analytics IoT Real Time Insight Customer Provides IBM Provides IBM/Partner Provides SI/Technology Partner Play Device Partner Partner Play
- 20. Satellite and dronedetection of stressed areas Satellite observation of farms. variability in greenness due to fertilizer deficiency Combine multiple data layers (IoT sensors, satellite, drone and weather data) to determine locations for variable rate fertilizer applications Drone imaging of a farm with variability in crop greenness
- 21. IBM & E& J Gallo Wines Precision analytics to improve crop yields while reducing water consumption ImpactInnovation ▪ 26% more yield in the precision area compared to conventionalone ▪ 11 % higher water efficiency ▪ 50 % higher uniformity ▪ Improved quality index (Brix value) ▪ Technology provided to allof Gallo’s vineyards provides $120M of annual value (100,000 acres x $1.0k)= $100M )
- 22. From precision agricultureto ‘EZ Farmer’ IOT brings inclusive access to real-time and predictive water and soil insights
- 23. IBM Metropulse Hyper-localinsights intothe diversity of food demand and supply A cloud-based service that applies cognitive computing to hyper-localised data sets to measure the pulse of a neighbourhood. Companies can dynamicallyrespond to consumer demand, such as making sure that specific food products stay in stock
- 24. © 2016 IBMCorporation Big data = insight
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- 26. IBM Food BlockchainConsortium
- 27. IBM Consortium forsequencing the supply chain
- 28. Farm, land, property advice Farm,land, property financing Farm,land, property insurance Finally,who wants to deliver the platform? Crop cycle advice Mixadvice Seed consults Timing suggestions Selling, buying Seed & bundling financing advice Seed & growth Best practices insurance Equipment proposals Dealership suggestions Maintenance & replacement alerts Equipment financing Equipment insurance Fertilizer proposals Pest control advice Regulation optimization Financing & insurance options Irrigation advice Distribution Special weather & timing alerts alerts Optimized seeding, harvesting timing Water procurement pricing optimization Harvest timing based on resale value Sell-through optimization consults Advanced contractors booking suggestions LT contracts Processing optimized Integrated planning Innovative ingredi ents insertion Co-operatives Value-add in opportunities food services Convenience Innovative value-add packaging ST supply Ready-to-cook Packaging End-to-end opportunities meal packages opportunities SCM management Retail ready packaging SC feed-back & seeding, Integration with and long-life Full value chain timing harvesting services suggestions Transport-ready End-market Restaurant packaging transparency ready-mixes Storage and transport optimization options LT contracts feed-forward Sell-through insights fertilization & Mixed harvest growing and home delivery packaging bench marking Retail-brand contracting & SC integration Retail alliance Long Term & Short Term usage patterns Regional insights Emerging needs Demographic shifts Restaurant Understanding (chains) direct of news and delivery advertising Land, Farm Plant Equipment Chemicals Irrigation Harvesting Processing Value-add Packaging Supply Chain Retail Consumption End-user & property activities Management patterns lifestyle Innovative experiences End- user needs & insights End-user suggestions End-user Influence Journey mapping insights
- 29. 5 important principles onthe journey § Embrace the whole chain – don’t forget the end user § Understand value creation – across all stakeholders § Act as a change project § Optimize for the benefit of all participants § Build a big vision for the long run – but start by prototyping Kilde: Digital vækst iFødevareklyngen
- 30. Kim Escherich escherich@dk.ibm.com +45 28804733 internetofthings.dk @kescherich | @danmark50 /in/escherich