Application of cloud based sensor data infrastructure for agricultural information service in Hokkaido Japan



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Application of cloud based sensor data infrastructure for agricultural information service in Hokkaido Japan APAN 36th Meeting 20 Aug 2014 HONDA Kiyoshi: Chubu University Apichon Witayangkurn: University of Tokyo Rassarin Chinnachodteeranun: Geomove Co., Ltd. Akihiro Yui, Takashi Seshimo: IHI Corp. Agriculture Information Service on Modeling and Scenario Simulation Data Integration on cloud system UAV Sensor Network Satellite RS Agri. Machines, Applicatio n records Cloud & Data Integration Weather Crop Model Model Calibration Comparison of Satellite LAI and Simulated LAI 5 LAI_sat 4 LAI Yield, Soil, etc. HPC (GPGPU, Cluster, GRID) LAI_sim 3 2 1 0 0 30 60 90 120 150 180 210 240 270 300 330 360 DOY Scenario Simulation Real Time Update Decision Making 1

Ubiquitous Field Sensor Network Small and Low-Cost Sensors New Field Platforms Mobile Internet Real-time field information from anywhere Disaster, Agriculture, Logistics, Security, etc. Monitoring Panel, Early Warning, Simulation Mobile Internet + Low Cost Sensor CO2: SenseAir Field Platform FieldServer: NARC Ubiquitous Field Sensor Network cloudsense Sensor Back-end Cloud Service Based on Int l Standard cloudsense Low Cost Implementation/ Operation and Interoperability Back-end Field Sensor Sensor Application Cloud Service 2

Standardization the key for interoperability and data integration n OGC ( Open Geo-Spatial Consortium) Standards on SWE ( Sensor Web Enablement ) n SOS ( Sensor Observation Service ) n SPS ( Sensor Planning Service ) n WNS ( Web Notification Service ) n Standard query/response by XML n Sensor Metadata( Information on Sensor ) Figure from http://52north.org n Sensor Data n Interoperability n Serve Data to SOS Compliant Applications n Monitoring Panel, Early Warning, Simulation System Fieldtouch Agricultural Information Service Platform n A Web Application. n Support Precision Farming by providing information services to farmers. n Development led by IHI. Chubu U, Geomove Co., Ltd. provides sensor cloud service, simulation and UAV technology 3

Fieldtouch ( cont d) A platform to integrate Satellite RS - RapidEye UAV Images Field Sensor Data Simulation agricultural practices OGC s Web Services WMS an SOS Improve productivity, quality and efficiency, cost saving Serving to 120 Farmers in Hokkaido Japan Tokachi Area, Hokkaido Japan Large scale agriculture Wheat, Potato, Soy beans, Sugar Beat, and other Active Farmers, keen to improve productivity 4

Fieldservers 8 Fieldservers and 3 Child Stations Temp, Humidity, Wind, Solar Radiation, VWC Field Sensor Data Fed to cloudsense A datafeeder access to each fieldserver every 10 min Meta data and Data served via SOS Adding and Modification is automatically reflected to field touch 5

Benefit of using SOS n Isolation of application development and physical sensor node setting virtualization n Quick Adding of sensor node to the Fieldtouch n Operating multiple nodes with different sensor configuration n Obtaining Location, Sensor kind, UOM via SOS Future Development n Data feed from other sensors n Elab s Fieldserver & Fieldtouch n Agriweather s Weather Bucket n NIAES Web n Meisei s Weather Station n Manual Field observation ( LAI, Spectrometer ) n Integrating UAV images vis SWE s SPS n Simulation integration n Commercial operation 6

UAV ( Unmanned Aerial Vehicle ) became realistic sensor platform for agriculture Monitoring of rice field at Aichi Irrigation Command Area in Handa City UAV Images to be integrated. Request and Obtaining via SWE s SPS (Sensor Planning Service ) 7

Conclusion n Cloud based sensor back-end service and OGC s standard enables quick deployment and flexible operation of sensor node n Heavy access in the morning n Efficiently utilized by farmers n Contribute to improvement of quality, production and income n Further development for sustainable operation 8