Data management and analytics

Data management and analytics

This Learning Object is part of Master AGRITECH EU – Digital Agriculture for Sustainable Development, an Italian one-year specialisation programme organised by University of Pisa, University of Macerata, National Research Council (CNR) and Quinn Consortium (Consorzio Quinn)

For more information about the programme and to enroll here

It is possible to enroll for the whole programme or for the single Learning Object (Module) you are interested in

Module details

The module covers the full data pipeline in modern agricultural settings, from storage and retrieval to analysis and decision-making. Students will explore database management and big data infrastructures, image-based and metadata-driven search, and Artificial Intelligence techniques — including supervised and unsupervised learning and neural networks — applied to agricultural datasets and multispectral imagery. The module also addresses how these tools integrate into farming management systems to support data-driven decisions across the agricultural value chain.


Proposer: University of Pisa (UNIPI)

Organization: University of Pisa (UNIPI), National Reasearch Council (CNR), University of Macerata (UNIMC)

Duration: 62h

ECTS: 5

Shortcut access code: No

Year of pubblication: 2026

Topics

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Subject areas: ,

Delivery methods: On Line

Teaching methods: Lectures, Working Group

Languages:

Learning objectives
  • Dataset for AI
  • Big Data
  • Data management and database
  • Search engines and data retrieval (for images and metadata)
  • Artificial intelligence (supervised and unsupervised)
  • Neural networks
  • Multispectral images
     
  • Images representation

    Overview and introduction to the module: images and their representation


    Description: The transformation of telecommunications : new network architectures for cyber physical systems
    Duration: 4h
    Teacher: Giordano (DII - Department of Information Engineering)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

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  • Big Data

    Parallel Computation basic concepts and map reduce theory, big data analytics


    Description: Parallel and distributed computing, agent based systems and excercises,big data analytics, data visualization
    Duration: 26h
    Teacher: Trasarti (CNR), Monreale (DI - Department of Computer Science), Rinzivillo (CNR)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

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  • Basics of image processing and analysis

    Geometric transformations,filtering,image enhancement,image registration;,image segmentation


    Description: Basics of image processing and analysis (geometric transformations; filtering; image enhanceemt; image registration; image segmentation; all topics accompanied by tutorials using open source software),case studies in agriculture
    Duration: 16h
    Teacher: Moroni (CNR)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

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  • Computer Vision & Applications in Agriculture

    Computer vision and CNNs for agricultural applications


    Description: Introduction to computer vision, convolutional neural networks,applications in agriculture, object detection
    Duration: 16h
    Teacher: Martinelli (CNR)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

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