An interdisciplinary team held a bootcamp to develop farmer-oriented innovation projects using open-source technologies like Arduino and Raspberry Pi. Four projects were developed by farmers and students to monitor various agricultural data through IoT sensors and provide alerts or analyses to farmers. The bootcamp achieved its goals of enabling participants to innovate using affordable open-source tools and providing a model for future collaboration between farmers, students, and experts to develop precision agriculture solutions.
1. Farmer-oriented
innovation: outcomes
from a first bootcamp
Jérôme DANTAN, Davide RIZZO, Fatma FOURATI, Michel DUBOIS, Mehdi JABER
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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2. Farmer-oriented innovation:
outcomes from a first bootcamp
Jérôme DANTAN, Davide RIZZO, Fatma FOURATI, Michel DUBOIS, Mehdi JABER
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Corresponding
author
Presenting
today
Information
Technologies
Agronomy,
data science
Management
science
Agricultural
sciences expert
Digital
innovation
An interdisciplinary team
@pievarino
4. Institut Polytechnique UniLaSalle
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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A private higher education establishment
2800 students
3 integrated degree
programs in Food &
Health, Geology &
Environment,
Agronomy and other
Bachelor and Master
degree programs
4 Academic and
Industrial Chairs
4 research groups
and several facilities member of the Lasallian education network
3 campuses in northern France:
Beauvais, Rouen, Rennes
8. Farm technology
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Important subset
of the agrifood
tech landscape,
often referred to as
‘agtech.’
Cosgrove E, Leclerc R, Burwood-Taylor L, Chauhan R (2018) AgFunder Agrifood Tech
Investing Report 2017. AgFunder
Farm Robotics, Mechanization &
Equipment. On-farm machinery,
automation, drone manufacturers,
grow equipment
Farm Management Software,
Sensing & IoT. Ag data capturing
devices, decision support software,
big data analytics
Novel Farming Systems, Ag
Biotechnology, Agribusiness
Marketplaces, Bioenergy &
Biomaterials, Farm-to-Consumer
eGrocery, etc.
15. Bootcamp overview
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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http://agrilab.unilasalle.fr/projets/projects/open-iot-in-smartfarming
o Agricultural data: an answer
to what question?
(D. Rizzo)
o Farm Open-source DIY
Internet of Things
(M. Jaber)
o Developing affordable
open-source IoT
(C.Pham)
o IoT connectivity examples
with Wolfram Mathematica,
Arduino & Raspberry
(P. Fonseca)
o Data science et Human-
machine interface with
Wolfram tools
(D. Birraux)
Step 1
Step 2
morning
Step 3
afternoon
Step 4
morning
Step 5
afternoon
Step 6
14-16:30 pm Introductory conferences
17-18:30 pm Farmer-oriented teams
DAY#1DAY#2DAY#3
designing: defining variables to be
monitored and expected DSS interface
learning: electronic components,
packaging, Arduino connectivity and
HMI, early prototypes
assembling the concept
prototypes
wrap-up and perspectives
16. Open innovation approach
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Boosted by the Hauts-de-France Social
and Digital Innovation regional program
INS’Pir http://www.hautsdefrance.fr/inspir/
Everything documented in a free and
open knowledge base shared under
Creative Commons licence:
http://agrilab.unilasalle.fr/projets/projects/open-iot-in-smartfarming
17. Common project outline
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Physical variable(s)
Sensor(s) Arduino &
electronics
Network
(cloud)
Database
HMI, machine learning,
data vizualization
Icons by Icons8 https://icons8.com
From the farm and field issues to
the farmer’s decision making
Prototyping activity
18. 4 farmer-oriented projects
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Decisio
Soil moisture monitoring to:
o manage flax sowing
o identify potatoes harvesting
time
iPatate
o Potato stocks quality
monitoring
o Remote management of
agricultural activities
SiloTeam
o Remaining quantity of food in
poultry food storage silos
monitoring
o Comparative display of the
filling of silos
VegData
o Early rot detecting in salads
o Network farms data sensors
in the same region to achieve
large data collection to feed
artificial intelligence system
http://agrilab.unilasalle.fr/projets/projects/open-iot-in-smartfarming
19. Decisio
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Field Protective housing
Arduino
Lora network module
Smartphone
Sensor Battery
Issue
Specifications
Implementation
Physical data Output
Soil moisture
monitoring to
manage:
o flax sowing
o potatoes vegetation
Soil moisture and
temperature,
moisture and air
temperature, foliar
development and
rainfall
o Flax: knowing the best period
for sowing.
o Potatoes: predicting the
stoppage of vegetation
growth and thus the harvest
o Soil temperature and moisture
sensors, measured every 15 minutes
o Data storing in a cloud database
o HMI/Data visualization
o Alerts/warning SMS
o Web access
Decisio sensor-to-OAD package
http://agrilab.unilasalle.fr/projets/projects/open-iot-in-smartfarming
20. iPatate
Issue
Specifications
Implementation
Physical data Output
Potato stocks quality
monitoring
Temperature, CO2,
humidity and phyto-
hormones
Intervention of the
operator
o Retrieve and sort
data
o Data analyses to
send alerts
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Final version of the installation of
sensors and transmitters / receivers
within the storage building
http://agrilab.unilasalle.fr/projets/projects/open-iot-in-smartfarming
21. Vegdata
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Issue
Specifications
Implementation
Physical data Output
Early rot
detecting in
salads
Temperature of both
air and soil and
humidity of both air
and soil
Raising soil moisture to
warn the farmer when the
moisture reaches a
threshold that requires
irrigation
o Protection for sensors
o 3 temperature and Humidity
sensors (atmosphere and soil)
o HMI/data visualization
Location of sensors on the salad and underground
http://agrilab.unilasalle.fr/projets/projects/open-iot-in-smartfarming
22. SiloTeam
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Issue
Specifications
Implementation
Physical data Output
Monitoring and
quantifying the
poultry food
remaining in storage
silos
Height of food
remaining in the silo
Exact tonnage of
food remaining in
the silos
o Algorithm calculating the filling rate
of the silo, as well as a comparative
display of the filling of every silos of
the farm
o HMI/data visualization
Comparative display of the filling of silos
http://agrilab.unilasalle.fr/projets/projects/open-iot-in-smartfarming
23. Conclusions
1 – Introduction
2 – Organization & main outcomes
3 – Take-home message
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
24. Opportunities & perspectives
Farmer-oriented innovation: outcomes from a first bootcamp ● Dantan et al.
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Future
challenges:
prototype Lora
network nodes and
gateways, deploy
Open TimeSeries
database platform,
putting all together
the four sensor
projects in the farms
o agronomy: enable farmers to
better monitor the
environment, thus to facilitate
the implementation of
precision farming
o economy: provide added
value for farmers, new
business models, startups
o technology: develop
predictive analyses, which
will require bigger data sets