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dc.contributorNadagoudar, Karanen_US
dc.contributorEl-Shamaa, Khaleden_US
dc.contributorAtassi, Layalen_US
dc.contributorLoew, Fabianen_US
dc.contributorSingh, Rajkumaren_US
dc.contributorOmary, Jalalen_US
dc.contributorBonaiuti, Enricoen_US
dc.contributorKoo, Jawooen_US
dc.contributorKing, Brianen_US
dc.creatorBiradar, Chandrashekharen_US
dc.date2018-01-19en_US
dc.date.accessioned2019-03-03T02:22:59Z
dc.date.available2019-03-03T02:22:59Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/5233e20be2f25a320efe697957c8e92een_US
dc.identifier.citationChandrashekhar Biradar, Karan Nadagoudar, Khaled El-Shamaa, Layal Atassi, Fabian Loew, Rajkumar Singh, Jalal Omary, Enrico Bonaiuti, Jawoo Koo, Brian King. (19/1/2018). Artificial Intelligence (AI) and Internet of Things (IoT) for Inclusive Agro-Ecosystems for Sustainable Development. Beirut, Lebanon.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/9583
dc.description.abstractThe technological advancements in agriculture have resulted in higher yields but lower nutritional value and ecological efficiency. Lesser innovations in later sectors have crippled our agroecosystems to meet the demands. Recent advances in earth observation system (EOS), openaccess (AO), artificial intelligence (AI) and machine learning (ML) along with smartphone enabled citizen science (CS) opened tremendous opportunity to address the gaps for demand-driven precision interventions across the scale (e.g., space, time and package). Such technological enablement for smallholder farmers and farms is very much needed to achieve the desired yield and agro-economy. While complexity of small landholdings, heavy and embedded-machinery is expensive and/or often not universal for diverse cropping. Therefore, it is necessary to bring insights from raw/big-data through a unified system leveraged by intelligent information processing to enhance the farm productivity and profits. The system address the market flux in response to supply-depend symmetry of the given commodities in the target zone. The proposed inclusive-integrated system gives power to farmer by leveraging the AI, ML, and IoT to give optimum solutions at famer's finger tips. Our aim is to reduce the resources use and enhance the agro-ecosystem productivity of farms and farmers. This multidimensional and interactive information will also help proper alignment of the factors at a manageable scale and affordable cost to benefits stallholders and support the sustainable development goals (SDGs).en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherInternational Center for Agricultural Research in the Dry Areas (ICARDA)en_US
dc.rightsCC-BY-NC-4.0en_US
dc.subjectagro-ecosystemsen_US
dc.titleArtificial Intelligence (AI) and Internet of Things (IoT) for Inclusive Agro-Ecosystems for Sustainable Developmenten_US
dc.typeConference Paperen_US
cg.creator.idBiradar, Chandrashekhar: 0000-0002-9532-9452en_US
cg.creator.idEl-Shamaa, Khaled: 0000-0002-7668-3798en_US
cg.creator.idAtassi, Layal: 0000-0002-7271-7591en_US
cg.creator.idLoew, Fabian: 0000-0002-0632-890Xen_US
cg.creator.idSingh, Rajkumar: 0000-0002-3576-8971en_US
cg.creator.idBonaiuti, Enrico: 0000-0002-4010-4141en_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocartificial intelligenceen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerData Grokren_US
cg.contributor.centerInternational Food Policy Research Institute - IFPRIen_US
cg.contributor.centerInternational Center for Tropical Agriculture - CIATen_US
cg.contributor.crpBig Data in Agriculture - BDAen_US
cg.contributor.funderInternational Center for Tropical Agriculture - CIATen_US
cg.contributor.projectCGIAR Platform for Big Data in Agricultureen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionGlobalen_US
cg.contactc.biradar@gmail.comen_US
dc.identifier.statusOpen accessen_US
mel.project.openhttp://bigdata.cgiar.org/en_US


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