Resultados de búsqueda - "data analytics"

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  1. Big data analytics enhances agribusines sustainability por Addom, Benjamin K.

    Publicado 2018
    “…Benjamin Addom, ICT4Ag Team Leader at CTA, shares his views on sustainable business models and big data analytics.…”
    Enlace del recurso
    Video
  2. Big data analytics for climate-smart agriculture in South Asia (Big Data 2 CSA): Developing data-driven and evidence-based solutions for problems constraining climate-smart agriculture in South Asia por CGIAR Research Program on Climate Change, Agriculture and Food Security

    Publicado 2019
    “…Alternative approaches utilizing large heterogeneous datasets, however, remain insufficiently explored, though they can represent a powerful source of technology and management performance information. The big data analytics for climate-smart agriculture in South Asia (Big Data 2 CSA) project responds to thelimitations of plot-based agronomy by developing digital data collection systems to source, data-mine and interpret a wide variety of primary agronomic management and socioeconomic data from tens of thousands of smallholder rice and wheat farmers in India, Nepal and Bangladesh. …”
    Enlace del recurso
    Otro
  3. Excellence in Agronomy por CGIAR Initiative on Excellence in Agronomy

    Publicado 2022
    “…We seek to leverage the power of science, data analytics and latest advances in digital solutions to reach larger numbers of farmers with the solutions they need, in a manner that is accessible and useable.…”
    Enlace del recurso
    Website
  4. Excellence in Agronomy por International Institute of Tropical Agriculture

    Publicado 2022
    “…We seek to leverage the power of science, data analytics and latest advances in digital solutions to reach larger numbers of farmers with the solutions they need, in a manner that is accessible and useable.…”
    Enlace del recurso
    Video
  5. CGIAR Excellence in Agronomy Initiative por CGIAR Excellence in Agronomy Initiative

    Publicado 2024
    “…EiA is supported by the CGIAR Big Data Platform and will combine big data analytics, new sensing technologies, geospatial decision tools, and farming systems research to come up with scalable agronomic innovations for agricultural development. …”
    Enlace del recurso
    Website
  6. Data Plaza: An interoperable platform for combining, analyzing, and visualizing research open data por Quirós, Carlos F., Arnaud, Elizabeth, Laporte, Marie-Angélique, Sousa, Kauê de, Etten, Jacob van

    Publicado 2023
    “…The objective is for this platform to become a one CGIAR data analytics platform and support making data ready fo artificial intelligence.…”
    Enlace del recurso
    Ponencia
  7. Delivering climate risk information to farmers at scale: the Intelligent agricultural Systems Advisory Tool (ISAT) por Rao, K.P.C., Dakshina Murthy, K., Dhulipala, R., Bhagyashree S.D., Das Gupta, Mithun, Sreepada, Soudamini, Whitbread, Anthony M.

    Publicado 2019
    “…Microsoft India developed a platform to access real time data from various ‘public’ sources, perform the data analytics, implement the decision tree and generate and disseminate messages to farmers and associated actors. …”
    Enlace del recurso
    Artículo preliminar
  8. Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension por Jones-Garcia, Eliot

    Publicado 2022
    “…The increasing capabilities of Artificial Intelligence-augmented data analytics present significant opportunities for agricultural extension organizations operating in the Global South. …”
    Enlace del recurso
    Informe técnico
  9. How ICTs are shaping sustainable and modern farming systems in India por Gakhar, Shalini, Rai, Anil, Sharma, Sheetal

    Publicado 2024
    “…After reaping the benefits of the Green Revolution, we are now poised to witness a new transformation through cutting-edge technologies of ICT, such as artificial intelligence (AI), the internet of things (IoT), robotics, edge computing, big data analytics, unmanned aerial vehicles (UAV), the blockchain, and remote sensors. …”
    Enlace del recurso
    Blog Post
  10. Hi tech support end to end drought monitoring and management system for South Asia por International Water Management Institute

    Publicado 2022
    “…The SADMS allows APIs access to integrate into a third-party platform for robust data analytics and decision making process.…”
    Enlace del recurso
    Video
  11. Elaboración de nuevos productos viníferos a través de la estratificación de calidad de uvas mediante la zonificación de áreas productivas del Valle del Itata

    Publicado 2021
    “…El proyecto abordará de manera integral con un equipo multidisciplinario, la producción de uvas y vinos, utilizando herramientas de Viticultura de Precisión, tales como: utilizando el procesamiento de imágenes satelitales Landsat, para obtener índices productivos y datos térmicos y mediante Data Analytics realizará una jerarquización de de zonas productivas homogéneas, utilizando Modelos Digitales de elevación (MDT), para obtener topografía y exposición de laderas a radiación solar, lo cual junto a datos productivos históricos del INDAP (asociado) permitirá definir perfiles de productores, por zonas edafo-climáticas homogéneas, análisis que abarcará toda el área del proyecto (328.000 ha). …”
    Enlace del recurso
    Proyectos
  12. International Certificate Course in Digital Agriculture por Gakhar, Shalini, Sharma, Sheetal, Patwar, Shelly, Arya, Satyajeet

    Publicado 2023
    “…Spanning seven weeks and 40 hours, including assignments, this course uniquely catered to the needs of those passionate about digital agriculture (DA), offering comprehensive insights into digital technologies, user-centered design principles, and data analytics to foster informed decision-making in agri-food systems. …”
    Enlace del recurso
    Informe técnico
  13. Machine learning and big data techniques for satellite-based rice phenology por Aguilar-Ariza, Andrés

    Publicado 2019
    “…Three machine-learning approaches (random forest, support vector machine, and gradient boosting trees) were trained with multitemporal NDVI data. Analytics from validation showed that the algorithms were able to estimate rice phases with performances above 0.94 in f-1 score. …”
    Enlace del recurso
    Tesis

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