big expectations from big data in the european agrifood sector€¦ · 01/01/2019 · big...
TRANSCRIPT
5th Technology ForumBig Data Session
16 May 2018
Big Expectations from Big Data in the European Agrifood Sector
G r i g o r i o s C h a t z i k o s t a s • H e a d o f B u s i n e s s D e v e l o p m e n t
D e p a r t m e n t • c h a t z i k o s t a s @ b i o s e n s e . r s
Ready, Tech, Grow: Agrifood & Emerging
Technologies
Mega Trends Driving Agrifood Transformation
Consumer preferences
Rising consumer demand for personalized, on-demand products and increasing awareness for product
traceability throughout the supply chain
Emerging technologies
Big inefficiencies suggest finding big opportunities in emerging technologies. On average, 35% of the initial
production is lost or wasted at different stages
New configurations in value chains
Growing trend towards horizontal and/or vertical consolidation across the
ecosystem, with new data technologies being a
powerful driver
Innovation Trigger
Peak of Inflated Expectations
Trough of Disillusionment
Slope of Enlightenment
Plateau of Productivity
BlockchainWater Trading
Indoor FarmingAmazon for Inputs
Fully AutonomousSynthetic Aperture Radar
On Plant SensorsDeep learningIn field wireless
Hyper-spectralUber for Tractors
Farm IoTSoil Sensors Machine Learning
DronesTraceability Platforms
Nano-SatellitesDashboardsScouting AppsMoisture sensorsHyper-local
weatherBig DataAerial Imagery
CloudFarm ERP
Satellite ImageryPrescriptions
VR
Soil SamplingIn cab display
Yield MonitorsNDVI
Autosteer
Precision Ag: The Big Data Landscape
WHAT’S READY? WHAT’S NEXT ?
Innovation Trigger
Peak of Inflated Expectations
Trough of Disillusionment
Slope of Enlightenment
Plateau of Productivity
BLOCKCHAIN
IN FIELD WIRELESS
FARM IOT
BIG DATA
Precision Ag: The Big Data Landscape
WHAT’S READY? WHAT’S NEXT ?
Turning Data into Decisions: How to
Manage Uncertainty and Rising End-user
Expectations
3 Pain Points of Big Data in FarmingHOW TO ENSURE BIG DATA BRINGS VALUE TO FARMERS
Soothing farmers’ concerns about data misuse while enabling data collection across the entire value chain;
Ensuring interoperability between applications & agri-services in building a robust Food + AgTech ecosystem;
Creating a framework that simplifies decision making in a wide range of business applications;
From big data to SMART dataSpecific. Measurable. Actionable. Relevant. Timely
> IDENTIFY key drivers of farmer satisfaction: production & profitability, environmental sustainability, social responsibility;
> DETAIL on-farm operations and processes & spot farmers’ pain points;
> USE good, reliable data to spot opportunities for improvement & provide a product or service as a solution to a specific problem;
Data buyers and farmers enter into
relationships wherein both can
participate in value creation.
Revenue is evenly split with farmers.
ROI GUARANTEE
An ag data collection and software
service, Farmobile empowers
farmers with complete year-over-
year data gathered in real-time and
data ownership
DATA AS A SERVICE
1
2
3Farmers decide whether to
approve offers. Data buyers such
as dealers, agronomists, crop
insurance agents only pay for the
information they desire.
FROM DATA TO PRODUCT
Buyers get a direct link for data
collection with baseline customers ,
utilizing unique field data to create
value and growth for their own clients
(e.g. AgI)
RISK VS. REWARD
4
5
6
Farmobile offers farmers legal
agreements that govern the
ownership and control of their
agronomic data
EXCLUSIVE OWNERSHIP
Farmers decide whether to approve
offers. Data buyers such as dealers,
agronomists, crop insurance agents
only pay for the information they
desire.
EQUITABLE TERMS
AgroSense Platform At-a-glanceA s ingle p lat form for personal ized dec is ion support in
crop monitor ing & planning of agr icul tural act iv i t ies
M O R E T H A N 8 0 0 0 U S E R S
Digital field records
Weather forecast
Satellite crop indices
Pest & plant diseases
Soil analysis overview
Overview of costs
Machinery calibration
Crop photo uploads
End-user Engagement: Delugged with Data, Hungry for Insights
Digital Farm for DemonstrationsSTRATEGIC COLLABORATION WITH KRIVA JA DOO, A REAL FARM SITUATED IN BACKA TOPOLA, SERBIA
Farmers need to see in order to believe
Proving ROI of smart farming technologies in real life conditions
Farmers are able to learn on-the-stop and free of charge how to use new smart farming technologies
Promoting “multi-actor” AgTech innovation ecosystem
Digital farm brings together various stakeholders and acts as a testbed for value-added products & services
Demonstrate, Engage & Make Meaningful Impact
A rich selection of equipment for a range of applications & AgroSens, decision support tool for data-driven farming
First Digital Farm in Serbia
PHYSICAL PART VIRTUAL PART
KRIVAJA, BAČKA TOPOLA
O P E N D AY S
A cross-cutting approach to diversityDIVERSITY & INCLUSIVENESS
We can do a lot, but we cannot do it alone.
Huge Diversity in the EcosystemGeeks/Farmers; Small farmers/Big Corporates; Scientists/Business People
No “One-size Fits All”Technologies; Business models; Communication strategies
The Essence of a Cross-Cutting ApproachEmbracing diversity; Managing Complexity; Building a Pan-European Network;
The Lean Multi-Actor ApproachIOF2020: BOOSTING END-USER ENGAGEMENT WITH IOT
ECOSYSTEM CHAIREND USER FEEDBACKInvolvement & Co-creation
MVP1
MVP2
MVP3
DEMO
BUSINESS CHAIRKPIs EVALUATIONMeasurement & Monitoring
TECHNOLOGY CHAIRIMPROVEMENTSFinetuning
IoF2020 Open CallLOOKING FOR HIGHLY IMPACTFUL & MARKET-DRIVEN IOT INNOVATIONS
* B U D G E T E U R 5 - 6 M I L L I O N
Jun 5, 2018
Sep 30, 2018
Open Call Launched
Oct 31, 2018 Jan 1, 2019
Dec 31, 2018
Evaluation & Selection
New Use Cases Start
Submission Deadline
Contracting & Prepayment
***The given information about the Open Call is for informational purposes only and cannot be considered as legally binging
Open Innovation in the Age of Big Data
Crowdsourcing Big Data Analytics
Using the knowledge and expertise of bright
individuals outside the organization to accelerate
internal innovation;
Accelerating Corporate Innovation
Tapping into diversity directly through online
open innovation platforms for idea generation &
solving complex business problems;
The crowd as an Innovation partner
Getting people to work on clearly identified challenges,
collaborate and submit solutions through open innovation platforms;
Open Innovation in Agrifood
No two seasons are the same! The 2017 challenge pertained to the choice of
seeds for planting, as one of the most important
decisions for agriculturalists
Syngenta: Open Innovation & Crowdsourcing Platform
Bringing predictive analytics
BioSense – the winner of the 2017 Syngenta Crop Challenge in Analytics
> The BioSense team offered an AI-based solution, which provides recommendations as to which sorts to pick depending on the position of the parcel & weather conditions;
> This is to secure greater yields, while reducing risks;
> The solution also takes into account the location of seed vendors, allowing distributors to minimize their transportation costs and plan the sales;
The 2017 Syngenta Crop ChallengeOPTIMIZING SOYBEAN PLANTING WITH PREDICTIVE ANALYTICS
The contest challenged entrants to develop a model that predicts the seed varieties farmers are most likely
to select;
“There was excellent clarity in the logic of the BioSense team’s submission. They put a great deal of thought and contemplation into a very complex problem, and then solved it systematically.”
- Joseph Byrum, Syngenta lead for the Crop Challenge committee
Big Data for Crop Structure Planning (i)BIG DATA CHALLENGES & OPPORTUNITIES
What to plant where?
Evolutionary Algorithm: Expertise from Syngenta Crop Challenge – 1st prize
570 combinations ≈ number of atoms in the Solar System
> 70 fields, 5 major crops (wheat, soybean, maize, sugar beet, sunflower)
> Many constraints = multidimensional solutions
The problem: which one to chose?
What to plant where
Big Data for Crop Structure Planning (ii)THE BUSINESS CASE: MAXIMIZING RISK/PROFIT RATIO (SHARPE RATIO)
No sugar beet – wheat; maize; soybean; sunflowerBenchmark: current strategy (22 22 6 14)
• Max profit: +64% profit, +9% risk (0 7 55 2)
• Min risk: +22% profit, -8% risk (9 4 26 25)
• Sharpe: +56% profit, +3% risk (0 4 51 9)
Hard constraints (at least 20% wheat)Improving farmer’s strategy (adjusting 10% of farms)
Taking into account farmer’s preferences
Production goals: ↑profit, ↓yield risk, ↓price risk, crop rotation, crop grouping, ↓pesticides, fertilizers
Trade off between the risk & profitGoals & Profit
***The graphic shows the tradeoff between risk & profit
The Future of AgTechINCLUSIVE. SUSTAINABLE. CIRCULAR.
La Matanza – A hundred year tradition rooted in sustainability
