This presentation was presented at the IEEE 5G Worldforum in a session 'Dialogues between 5G/B5G and Vertical Domains: AI for Intelligent Services. Several use cases in Food Systems that use 5G are presented of which the 'weed detection robot' in more detail. Enabling factors and recommendations for the use of 5G to create intelligent services using AI are discussed.

1. AI for intelligent services in Food Systems
Sjaak Wolfert, Mireille van Hilten
IEEE 5G World Forum, Dialogues with the verticals, 15 Oct. 2020

2. Agro Food Robotics and AI
2
https://www.youtube.com/watch?v=68_zvFibxds

3. To explore
the potential
of nature to
improve the
quality of life
Wageningen mission
Digital Innovation
We bring the right partners together
who step-by-step develop digital
solutions, supported by state-of-
the-art knowledge on:
- data science
- information modelling and
management
- business modelling, governance,
and ethics

4. A vision on the application of AI in Food Systems
Successful Application of
Artificial Intelligence for
Sustainable Food Systems
Technically
robust
Socio-Economically
feasible
Socially acceptable
Ethically desirable
Human-centric
Fit-for-purpose
Explainable
Screening/auditing
Risk analysis
Power distribution
Labour effects
Human-robot
Inclusiveness
Discrimination
Tracking

5. Food Systems are increasingly being digitized
Smart Sensing
& monitoring
Smart Control
Smart Analysis
& Planning

6. Potential 5G connectivity benefits
Smart Sensing
& monitoring
Smart Control
Smart Analysis
& Planning
Edge computing for latency-sensitive
applications:
• storage and governance closer to the
farmer
• origin/certification information unlocked
to consumers.
• real-time product location
• monitoring systems: mobile apps, virtual and
augmented reality
• farmer's alerts with edge computing
• early warning in case of food incidents
• rescheduling i.c. unexpected food quality deviations
• product quality simulation based on ambient
conditions
• remote controllers for irrigation systems,
fertiliser systems, climate controllers,
harvesting systems, etc.
• achieve 99.999% accuracy with 5G
infrastructure with low risk

7. Exploring 5G use cases for Food Systems
7
Aggregation level
Farm system
Food system
Cross-sectoralrural area
Cyber-physical
Management cycle
Monitoring
Analysis & planning
Control
Decision-making level
Individual
(business/consumer)
Supply chain (food
integrity)
Public (society/
government)
Use case typology

8. 5G smart farming applications
8
This Photo by Unknown Author is licensed under CC BY-NC
Weed Detection
Robot
Real-time haulm
killing drone
Water quality
measurements 5Groningen
5G Rural Integrated
Testbed (5GRIT)
5G Range for
remote areas
Smart Farm
Innovation Valleys

9. Weed detection robot (Netherlands)
9
Autonomous weed robot: cameras and spot sprayer
attached to the vehicle to control plant specific
weeds.
Detection is a power- and data consuming operation
that requires costly hardware.
 Offloading computational operations and data
storage to a nearby infrastructure (cloud computing)
reduces costs and energy consumption to extend
operational time in the field. Photo 1 Weed detection robot (“Agrointelli Robotti
spuit plant-specifiek | LandbouwMechanisatie,”
n.d.)
Performance
• > 90% of weeds accurately detected and sprayed while < 5% of the main crop
sugar beet was sprayed incorrectly.
• Uplink 120 Mbps and 25 ms latency (upload images, processing images and
downloading locations of plants)

10. Weed detection robot – use case analysis
10
Aggregation level Farm system
Food system
Cross-sectoralrural area
Cyber-Physical
Management cycle
Monitoring
Analysis & planning
Control
Decision-making
level
Individual
(business/consumer)
Supply chain (food
integrity)
Public (society/
government)






11. 11
33 use case projects
>> 12 future 5G use cases
Source: www.iof2020.eu/trials
Internet of
Food and
Farm 2020
Innovation Action:
2017 - 2020
30 M€ funding by
DG-CNCT/AGRI
Large-scale
uptake of IoT in
the European
farming and food
sector

12.  Increased use of open (public) data, private farmer data and data from
service providers (e.g. contractors, soil laboratories, agribusiness)
 Ensuring interoperability by using standards & solid cyber security measures
 New business models for mobile operators (network sharing and slicing) and
the monetisation of data for all parties involved
 Sponsoring mobile traffic for rural areas to ensure fairness and inclusiveness
 Policy changes aiming at increasing the quality of life in rural areas and
continued Public Private Partnership (PPP) initiatives
 Ecosystem building as key enabler with local Digital Innovation Hubs (DIHs)
as a one-stop shop for farmers, investors, incubators, technology providers
Enabling factors for 5G uptake of in agri-food
12

13. Recommendations to leapfrog development
13
Scenario
I 5G implementations
available
II IoT implementations
available, without
5G
III No Smart Farming
and Food production
applied
Aggregation level Decision-making level
Management cycle
Extend from farm
level to food system
or cross-sectoral/rural
Close management
cycle by including
control mechanisms
Extend individual business
to supply chain and/or
public decision-making
Start at the farm
level to explore the
benefits of 5G
Start at monitoring
level, gradually
expand to analysis
and control
Start at individual business
decision-making level to
explore the benefits of 5G
Identify actors at
different levels that
want to start with
smart farming and
food production
Start at the
monitoring level
with most promising
technology
Start at the individual
business decision-making
level with most promising
technology

14. Thanks for your
attention!
14
Dr. J. (Sjaak) Wolfert
Strategic Sr. Scientist Digital Innovation in Agri-Food
Wageningen University & Research
sjaak.wolfert@wur.nl