Management and enhancement of agricultural data

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Client

Precision agriculture XLKey inc.

Collaborators

University of Sherbrooke, Rosecape, Cédric Bouffard, agronomist

Funding

National Research Council of Canada Industrial Research Assistance Program (NRC-IRAP)

Objective

Precision agriculture XLKey inc. is an agricultural company whose mission is to democratize precision agriculture for agricultural producers. With a large quantity of geospatial data from various sources to process, analyze and store, XLKey wanted to set up a geospatial database infrastructure and automated processing chains to respond quickly and efficiently to their various mandates. The CGQ’s mandate was to collaborate in the implementation of a geospatial data infrastructure and to develop geospatial processing and analysis tools adapted to the needs of agricultural data management and enhancement.

Methodology

Developing a data infrastructure plan

  1. Exploration and understanding of the business domain.
  2. Exploration of available data sources.
  3. Exploration of desired results, analyses and data structures.
  4. Gather and evaluate technical and business requirements.
  5. Brainstorming and ideation of technological solutions to meet technical requirements.
  6. Identification of technological risks.
  7. Development of technical requirements.
  8. Development of a validation plan.
  9. Development of a data infrastructure plan and roadmap.

Design of a data infrastructure prototype

  1. Choice of cloud platform and database management system.
  2. Implementation of cloud platform and database.
  3. Geospatial database structural and logical design and revision.
  4. Set up storage infrastructure.
  5. Testing of the infrastructure with a real dataset.
  6. Query testing and visualization via a Geographic Information System (GIS).

Creation of tools to optimize and automate various geospatial processes and analyses

  1. Automation of agricultural data collection, analysis and optimization.
  2. Automation of yield evaluation and agronomic analysis.
  3. Development of automated decision-support tools to help agronomists develop agronomic prescriptions.
  4. Development of a dashboard for data visualization and sharing.
  5. Writing of user guides and technical reports.

Equipment

The project is based on the use of cloud platforms to store, process and publish data in the form of maps on the Internet.

Field

Resource management

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