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Toward Global Agricultural Cloud
Masayuki HIRAFUJI* ** Yasuyuki HAMADA* Tomokazu YOSHIDA* Atsushi ITOH * Takuji KIURA * * NARO National Agriculture and Food Research Organization ** University of Tsukuba
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“Big Data” Has Been Dream in Agriculture
Plant growth is complex system. Environment is complex system. Maximization of income Minimization of pollution Maximization of plant growth Modeling by learning Analysis between genome and phonotype
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Nonlinear Regression Models Using Artificial Neural Networks (studied since 20 years ago)
Predicted Yield Recommendation of fertilizer … Last year’s application of fertilizer Accumulated air temperature. Accumulated soil temperature Accumulated soil moisture Last year’s yield
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Field Servers for Continuous Data Collection
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Low-cost USB DNA Sequencer
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Nanopore Technology
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More phenotypic data is needed for breeding.
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Phenomics vs. Genomics Gene + ome = Genome Genome + ics = Genomics Phenotype + ome = Phenome Phenome + ics = Phenomics
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Genome Data >> Phenome Data by High-throughput Phenotyping
Nanopore Sequencer Sensors in Fields Genotypic Data << Phenome Data Environment Data Genome Data >> Phenome Data Environment Data
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by Open Field Server (Open-FS)
Massive Deployment by Open Field Server (Open-FS) Wi-Fi LED garden light with IR sensor Solar panel Photo sensors Inside temperature sensor Soil temperature sensor Soil moisture sensor
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Field Twitter (Open-FS) Has Been Improved.
樹体水分センサ
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Towards A Field Phenomics Center
Wi-Fi Router 1km Phenotype data Calibration data for remote sensing Memuro Campus of HARC, NARO
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Tweeting data
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Tweeting data
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Tweeting data
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Collecting Microscopic Data by A Smartphone with A Macro Lens
A macro lens for iPhone Stomata on beet leaves can be measured.
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Products with Twitter
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Plant Sensor
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Data of Agricultural Machinery
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Data stream on agricultural machinery
Petition (GPS) Speed Power Fuel consumption Steering Vibration Yield Fertilizer Chemical
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Reprinted from the Proceeding of AgEng 2011 , pp.294, 2011
XML by iGreen Project for Agricultural Machine EU (Germany) leading. USA has a same project (AgGateway) ・ Reprinted from the Proceeding of AgEng 2011 , pp.294, 2011
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Farm management data
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Contents of FIX-pms Common Data Format for Farm Management Data
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How Can We Combine Data? API of Cloud Services Can Be A Method.
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Let’s Make Big Data for Agriculture!
Applicayions Developing New Businesses Decision Support System Precision Farming GAP Models API (Application Interface) New Apps and Businesses CLOP: CLoud Open Platform in agriculture API API API API Consortium Faming Data Field Data Sensor data of Agr-Machines Others 移動監視 SNS Smartphones UAV Satellites etc. Sensor Networks Such As Field Server ISO11783
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All Data Provided As API
API of Cloud Services Satellites UAV Smartphone Variable rate fertilization Harvester equipped with yield sensor Sensor data
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Mashape: Cloud API Hub
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Mash-Up Using API for Agricultural Data (FIX-pms)
on CLOP FIX FARMS APRAS
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Big Data Will Be Created by Using API of Apps
FIX FARMS APRAS
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The Best Condition Can Be Found on Nonlinear Models
Predicted yield Big data Yield Fertilizer Soil temperature Soil moisture : … Last year’s yield Last year’s application of fertilizer This year’s application of fertilizer Accumulated soil moisture
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Conclusion CLOP is conceptual framework for API mash-up.
CLOP must be flexible, and will include all. ANN can utilize big data. ICT companies should provide open API. Let’s make big data together. Let’s make API of agricultural apps. Let’s open “How to use API”.
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