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9/25/2014
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Smart farming and precision agriculture:management in the cloud?
Prof. dr. ir. Josse De BaerdemaekerDepartment of Biosystems
Division MeBioSKULeuven, Belgium
Field to fork (plot to plate) Fork to field (plate to plot)
„Precision Farming“ more than “Site-specific Farming”
Automateddata acquisition
Fleetmanagement
Site specific Fieldroboticsfarming
Fieldbooks and
Administration
Quality management
Farm management
Tillage
Spraying
Irrigation
Harvesting(with online decision)
Crop management
Route planning
Location monitoring
Location monitoringwith map-matching
Fleet member controland navigation
Teleservice
Machine management
Implement control/
Manned guiding vehicleand unmannedfollowing vehicles
Unmanned vehiclesof existing concepts
Unmanned vehiclesof new specialisedconcepts
Labour management
Traceability (documentation)
Basic data forPrecision Farming
On-farmresearch
bookkeeping Automatic guidanceDrilling
Fertilizing
Precision farming domains *
„Precision Farming“ more than “Site-specific Farming”„Precision Farming“ more than “Site-specific Farming”
Auernhammer, 2011, ACPA, JP
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How is Precision Agriculture being Re-Defined ?
large crops agriculture, US bias
Handling Big DataHow, Who?
Marc Vanacht at ISTPA 2014, Beijing, September 2014
Marc Vanacht at ISTPA 2014, Beijing, September 2014
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Marc Vanacht at ISTPA 2014, Beijing, September 2014
Marc Vanacht at ISTPA 2014, Beijing, September 2014
Measuring and modeling tools that fit the length of the cycle
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Marc Vanacht at ISTPA 2014, Beijing, September 2014
Marc Vanacht at ISTPA 2014, Beijing, September 2014
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Marc Vanacht at ISTPA 2014, Beijing, September 2014
Marc Vanacht at ISTPA 2014, Beijing, September 2014
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Marc Vanacht at ISTPA 2014, Beijing, September 2014
CONFIDENTIAL
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Where are the data?Where are the models ?
Where is the information?Who does the analysis?
Who suggests a decision?
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http://en.wikipedia.org/wiki/Cloud_computing
Cloud computing is internet-based computing in which large groups of remote servers are networked to allow sharing of data-processing tasks, centralized data storage, and online access to computer services or resources. Clouds can be classified as public, private or hybrid."The NIST Definition of Cloud Computing" . National Institute of Standards and Technology. Retrieved 24 July 2011 by Wkipedia.
Cloud computing
http://en.wikipedia.org/wiki/Cloud_computing
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Futuro de Monitoreo y Monitoreo de Cultivos
(Ejemplo Viñedos)
Mapas de Pre-
Automáticos
Mapas de Pre-Cosecha
Automáticos
Mapas de Cosecha
Modelos Espaciale
s de Patrones Predictiv
os
Visión Integrada
Diagnostico de Enologo y Viticultor
Riego
Teledetección
Calidad
Rendimiento
Suelo
Clima
Monitoreo Cercano
HPC (GPGPU, Cluster, GRID)
Scenario Simulation
Satellite RS Sensor Network
Real Time Update
Cloud & Data Integration
Model Calibration
Comparison of Satellite LAI and Simulated LAI
0
1
2
3
4
5
0 30 60 90 120 150 180 210 240 270 300 330 360
DOY
LA
I
LAI_sat
LAI_sim
UAV
Agri. Machines, Application records
Yield, Soil, etc.
Weather
Crop Model
Decision Making
Decision support by multiplatform data (Unv. Tokyo)
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Precision Farming – “Ag-Machinery and Cloud Computing”
ISO 11783
DIN 9684
Farm Management Information System
Task Controller
GPSNMEA 2000
TractorECU
ImplementController
VirtualTerminal
Realtime-Approach with
map overlay
Map + rules(requires ISOBUS extension)
In-fieldController
Mapping-Approach
Map with Set points(part of ISOBUS)
Realtime-Approach Rules
(requires ISOBUS extension)
On-line Sensor Soil Parameter
On-line Sensor Plant Parameter
AgMac-Server
Web-Services
File Server
Soil Services
Weather Services
Extension Services
Fleet Management Services
Book keeping Services
Farm Management Services
… Services
Auernhammer, 2011, ACPA, JP
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Monsanto Integrated Farming Systems
• Provide farmers with field-by-field recommendations for their farm,o ways to increase yieldo optimize inputs o enhance sustainability
• FieldScriptsSM:
o provide a hybrid match and variable rate seeding prescription customized for each farmer’s field
o Delivered wirelessly to the farmer through the FieldViewPlus app on the iPad
• Future
o crop protection, fertility and water based on predictive analytics
http://www.monsanto.com/sitecollectiondocuments/overview-of-integrated-farming-systems.pdf
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Pesticide Application Management
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CONFIDENTIAL
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Now start using your data!
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Smart farming example: egg farmsLay-Insight functionalities
www.porphyrio.com
www.porphyrio.com
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Users testify
“Good management depends on the ease of the management.”
“Lay-Insight gives me more control on my production, this is also reflected in the technical results” testifies Ward Hendrikx (Farm Manager, B).
With Lay-Insight egg production increased with 4% whilst feed
intake decreased with 1.5%.
“Daily insight in how we are doing – a great progress when you know we were always overtaken by events.” Peter Janssen (Farm Manager, NL),
www.porphyrio.com
China: Hongxing state farm FMIS
• Developed by NERCITAo Developed over 5 yr period (since 2009?)o At a given moment 180 persons involved
• Integratedo Telemetryo Fleet managemento Agronomy
• Satelite• Soil sampling and maps• Fertilizer recommendations + as applied• Yield maps• Disease and pests scouting• Ndvi scouting for N from satelite, machine, backpack• Sensor networks for real time monitoring of crops• Aerial applications possible
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China: Hongxing state farm FMIS
• Oracle database• ESRI for GIS• Java programming language• Library based menu’s, services list (each piece of
equipment is a service), registered pest control products, fertilizer formulations, micro-nutrients
• Cloud- ready, real time, 1 sec response time for a standard query
• Hierarchical access control (function, region,…)• Operates today on 11 farms, each 30000ha (total >
330000 ha)• ? More integrated and more powerful than JD, Trimble-
CNH, Agco-topcon, BASF ?
Cloud computing for agriculture• Clouds will help farmers to increase operationalefficiencies at reduced costs
• Up‐font investments (storage, maintenance) can be reduced
• Clouds are already in use for carriers and others (see iCloud from Apple)
• User discipline required for safe use(?)• Less IT skills required for farmers• Use of latest mobile devices is much easier• Updating of management software becomes easier• Software for decision making in PA to be adapted to local or regional conditions
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Cloud computing for agriculture
• Real time access to data, analysis or decision making using smartphones, tablets and computers.
• Real‐time management including planning, purchasing, planting, harvesting, marketing and inventory control.
• Disadvantage: dependency on a specific service provider?
• Data can be shared with advisors or management consultants
• Information is safe and secure against a crash of your computer
• Standardization of format for all data suppliers/users is required.
Advantages of cloud computing
• Cost Efficient in most cases
• Almost Unlimited Storage
• Backup and Recovery
• Automatic Software Integration
• Easy Access to Information from everywhere
• Quick Deployment
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Disdvantages of cloud computing
• Technical Issues: prone to outages
• Security in the Cloud
• Prone to Attack
• Dependency and loss of control
• Migration to a different Cloud Service Provider
• Knowledge And Integration
48
Esquema Conceptual de “CLOP”
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Acknowlegdements
• For this presentation use was made of the following sources:
o http://www.smartagrimatics.eu/Conference-Information/Programme#FarmingintheCloud
o Marc Vanacht ([email protected])
o http://www.conserviscorp.com/
o http://www.porphyrio.com/
