Presentation for a group of employees of Centric, a large software consultancy company. It provides an illustration of how IoT is currently being developed in farming, agri-logistics and food consumption. It also addresses the technical and organizational challenges that have to be overcome to make IoT application in agri-food a success. Open platforms and software development and above all appropriate business models are key issues that have to be addressed. The new EU-project "Internet of Food and Farm 2020" will address these issues by fostering a collaborative IoT ecosystem to upscale the use of IoT in agri-food.

1. Internet of Things in the Agri-Food sector
Sjaak Wolfert
Sr. Scientist Information management & ICT in Agri-Food
Centric Kennis- en Innovatiesessie, Gouda, 28 September 2016

2. Your image of farming?

3. Is this the actual image?

4. Wat doen wij op het gebied van
informatiemanagement en ICT?
Missie: wetenschappelijke ondersteuning van de agri-food
business bij het implementeren van ICT-oplossingen door:
 Analyse – wat zijn de ICT-ontwikkelingen en wat
betekent dat voor uw bedrijf(stak)?
 Ontwerp – hoe zou de ICT-oplossing er uit moeten
zien? (referentie-architectuur en infrastructuur)
 Implementatie – d.m.v. pilots prototype-oplossingen
ontwikkelen, veelal in sector-brede of -overstijgende
publiek-private projecten

5. Future Internet PPP – 300 M€ EU funding
5

6. FIWARE Generic Enablers

7. Brief history on FIWAREAgri-Food
2011-2013: SmartAgriFood - a FIWARE-based conceptual architecture
and prototype applications (5 M€)
2013-2015: FIspace – B2B business collaboration platform for agri-food
& logistics (+ apps) (13.5 M€)
2014-2016: Accelerators: SmartAgriFood2, FInish, FRACTALS (~17 M€)
- 125 apps/start-ups based on FIWARE/FIspace
Sep. 2016: FIWARE Foundation established with 3 verticals:
Smart Cities, Industry and Agri-Food
2017-2020: IoF2020 – The Internet of Food and Farm (30 M€) - IoT
large-scale pilot for smart farming and food security

8. ICT-induced innovations in the Agri-Food sector
Precision Farming Better management Segment Cons. supportService ++
Open farm management systems
with specific apps
Distance-advise on diseases etc.
Computer-aided advise and
decisions
Regionally pooled data analysis
for science and advise
Personalized advise
with new apps
Online shops
Integrated supply chains
feedback consumer-producer
Measure, pay
sustainability
Better T&T*
Paperless chain
Store
replenishment
Category
management
Sustainability HealthSafety + TransparencyFeed the growing world
LoyaltySmall Cost priceGRIN Service Cope with retail
Transport Transport Transport
Input industries
Farmer Food processor Retail / consumerSoftware
Provider
Logistic
solution
providers
*Tracking and Tracing

9. FI-Ware enabled
Cloud Platform
Cloud
Information
systems
SmartAgriFood: conceptual cloud architecture
sensors
actuators
data sources
(‘Internet of Things’)
local
Information systems
App store
Services
Spraying Advisory
Services
Meteorological
Service
State and Policy
Information Service
Consumer Food
safety service
E-agriculturist Service
for spraying potatoes
Machine Breakdown
Service
Transport
User’s
devices
Other
sources

10. smart sensing
& monitoring
smart analysis
& planning
smart control
Smart Farming: closing the cyber-physical
management cycle
BIG
DATA

11. Precision Agriculture
Closing the whole management cycle is complex and difficult  adoption is still low

12. Ag Equipment: mobile networks
• Tractor and Implement are acting as one network
• Always connected!
Cloud / Internet

13. PAGE13
WWW.CONNECTERRA.IO
Our solution: The Dairy Monitor
Complete animal healthcare in one device.
Based on sensor data we are able to provide the farmer with valuable insights and actions
Heat and Health Detection
Farmer Insights
Location Services
No more graphs to understand,
the system tells you what to do!
Track animal movements and
grazing habits to enable
organic certifications
Early detection of heat and
health issues improves
productivity by 20%
Sensors
Algorithms run
in the cloud
Insights &
actions

14. Involving the entire supply chain network
and beyond
Source: Hisense.com
Smart Farming
Smart Logistics
tracking/& tracing
Domotics Health
Fitness/Well-being

15. Cloud Event Management System
Location A Location B
Virtual
Plant
Virtual
Location A
Virtual
Location B
Environ
ment
update
Plant
location
update
Environ
ment
update

16. Tracking and Tracing and Meat Awareness (TTAM)

17. What needs to happen behind the scenes...

18. Event Data Repository
Registering event data with EPC* standard
Why
e.g. Deliver
What
e.g. Pallet EPC1, EPC2,.., etc.
(GIAI)
Where
e.g. door in distribution center
(GLN)
When
e.g. 1.06.2016 08:46:00 UTC+1
*EPC standard is founded by GS1, but is now ISO standard

19. Smart Food Awareness
To satisfy needs of each consumer by
providing transparent and tailored
information about agri-food products.
I am a Royal Gala apple
from south Spain, I was
grown without
pesticides following
organic farming criteria,
I have been here for 1
day, my carbon footprint
is 1,2 kg CO2e.
I am a self-
conscious
consumer that
wants to now
where my food
comes from and
how it is produced

20. App store
From conceptual architecture & prototypes to a real software platform
and Apps
Services
sensors
actuators
data sources
(‘Internet of Things’)
Local
ISs
Spraying Advisory
Services
Meteorological
Service
State and Policy
Information Service
Consumer Food
safety service
E-agriculturist Service
for spraying potatoes
FI-Ware enabled
Cloud Platform
Machine Breakdown
Service
User’s
devices
Other
sources
Cloud
IS
Transport
I2ND
IoT
IoC
IoS
S&T
GENERIC ENABLERS
Base Technologies
Validation
T270: Security, Privacy, Trust Framework: SPT (KOC)
T250: System & Data Integration
(ATOS)
T240: B2B Collaboration Core
(IBM)
T230: App Store (IBM)
T220: User Front-End (ATOS)
T260:OperatingEnvironment
(IBM)
T280:SoftwareDevelopmentToolkit:
SDK(ATOS)

21. FIspace platform High Level Architecture
I2ND
IoT
IoC
IoS
S&T
GENERIC ENABLERS
Base Technologies
Validation
1. Crop Protection
Information Sharing
2. Greenhouse
Management &
Control
3. Fish Distribution &
(Re-)Planning
4. Fresh Fruit and
Vegetables QA
5. Flowers & Plants SC
Chain Monitoring
6. Meat Information
Provenance
7. Import & Export of
Consumer Goods
8. Tailored Information
for Consumers
Trials:
Security, Privacy, Trust Framework: SPT
System & Data Integration
B2B Collaboration Core
App Store
User Front-EndOperatingEnvironment
SoftwareDevelopmentToolkit:SDK

22. FIspace approach: Software Mass Customisation
FIspace
App Store
My FIspace (BCM)
Develop
Apps
Pre-configure
User Systems
Customize &
Use Systems
FIspace Platform
Single App
Configuration
App developer Business Architect End User

23. Example: Spraying Scenario
Scenario: get expert advice for spraying to handle disease on tomatoes
State AuthorityFranz Farmer Ed Expert
Spraying
(follow advice)
Create
Advice
Approval
Request
Advice
CollaborativeBusinessProcessBack-EndSystems
Farm / GH
Management
Systems
Sensor Network
in the Greenhouse
Agronomist
Expert System
Regulations &
Approval System
1
2
3
FIspace App
‘Weather
Information’
FIspace App
‘Spraying Expert
Advice’
FIspace App
‘Spraying
Certification’
product type, etc.
sensor data
(access details)
suggested
chemical
advice details
certification
details
23

24. Redefining Industry Boundaries (1/2)
(according to Porter and Heppelmann, Harvard Business Review, 2014)
24
3. Smart, connected product
+
+
+
2. Smart Product
1. Product

25. Redefining Industry Boundaries (2/2)
(according to Porter and Heppelmann, Harvard Business Review, 2014)
25
5. System of systems
farm
management
system
farm
equipment
system
weather
data
system
irrigation
system
seed
optimizing
system
field
sensors
irrigation
nodes
irrigation
application
seed
optimization
application
farm
performance
database
seed
database
weather data
application
weather
forecasts
weather
maps
rain, humidity,
temperature sensors
farm
equipment
system
planters
tillers
combine
harvesters
4. Product system

26. Redefining Industry Boundaries (2/2)
(according to Porter and Heppelmann, Harvard Business Review, 2014)
26
5. System of systems
farm
management
system
farm
equipment
system
weather
data
system
irrigation
system
seed
optimizing
system
field
sensors
irrigation
nodes
irrigation
application
seed
optimization
application
farm
performance
database
seed
database
weather data
application
weather
forecasts
weather
maps
rain, humidity,
temperature sensors
farm
equipment
system
planters
tillers
combine
harvesters
4. Product system
Your company

27. Redefining Industry Boundaries (2/2)
(according to Porter and Heppelmann, Harvard Business Review, 2014)
27
5. System of systems
farm
management
system
farm
equipment
system
weather
data
system
irrigation
system
seed
optimizing
system
field
sensors
irrigation
nodes
irrigation
application
seed
optimization
application
farm
performance
database
seed
database
weather data
application
weather
forecasts
weather
maps
rain, humidity,
temperature sensors
farm
equipment
system
planters
tillers
combine
harvesters
4. Product system
Your company
Farmer: how many
platforms must I use?
Developer: on how many
platforms should I offer
my solution?
Platform owner: how
many connections do I
need to maintain?

28. Battlefield of IoT, Big Data and Farming
Farm
Farm
Farm
Farm
Data
Start-ups
Farming
Cooperatives
Open Ag Data
Alliance
...
AgBusiness
Monsanto
Cargill
Dupont
...
Tech
Companies
Google
IBM
Oracle
...
Ag Tech
John Deere
Trimble
Precision planting
...
Tech
Start-upsFarm
Tech
Start-ups
Data
Start-upsVenture
Capital
Anterra
Founders Fund
Kleiner Perkins
...
Farm

29. New Business Models based on Big Data
See: Arent van 't Spijker: "The New Oil - using innovative business models to turn data into profit“, 2014
 Basic data sales
● commercial equivalent of open data (e.g. FarmMobile)
 Product innovation
● use data to improve your product (machinery industry, e.g. John
Deere, Lely’s milking robots)
 Commodity swap
● data for data (e.g. between farmers and (food) processors to
increase service component)
 Value net creation
● pool data from the same consumer (e.g. AgriPlace)
 Value chain integration
● use data to control the whole chain (e.g. Monsanto’s Fieldscript)

30. Example: Monsanto Fieldscripts
30
PRESCRIPTIVE
FARMING
based on
VARIABLE RATE
APPLICATION

31. DATA-FAIR:
Open Software
Ecosystem
Stakeholders
Platforms
Apps + services
Knowledge models
Security, Privacy, Trust
Business models
Data sharing
Possible example of open collaboration
Farmer
Open Architecture & Infrastructure
Event-driven, Configurable, Customizable
Standards & Open Datasets
Real-time data sharing
IoT layer

32. Challenges to overcome
 Interoperability between IoT devices, applications and
platforms – open architectures, standards, etc.
 Development of IoT for harsh environments - open air,
dust, living animals, etc.
 Reliable and stable wireless communication and energy-
efficient technologies - e.g. LoRa, Sigfox
 Appropriate business models to boost use of IoT
 Governance issues: security, privacy and trust
 Create a large-scale, sustainable, collaborative IoT
ecosystem
32

33. Internet of Food and Farm 2020
2017-2020 - 70+ partners - 30M€ funding

34. IoF2020 – Large Scale Pilot

35. Wrap-up
 Agri-Food chains become more technology/data-driven
● Probably causes major shifts in roles and power relations among
different players in agri-food chain networks
● Open infrastructure and software development and business
models are key issues
 Two extreme scenarios:
1. Strong integrated supply chain in which
farmer is franchiser/contractor with limited freedom
2. Open collaboration network in which a farmer is
empowered through easier switch between
suppliers and customers
Reality somewhere in between?
Farmer
Farmer

36. Thanks for your
attention!
Questions?
More information
sjaak.wolfert@wur.nl
nl.linkedin.com/in/sjaakwolfert/
Twitter: @sjaakwolfert
http://www.slideshare.net/SjaakWolfert