Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases

Nyi Nyi Htun*, Diego Rojo, Jeroen Ooge, Robin De Croon, Aikaterini Kasimati, Katrien Verbert

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Decision support systems (DSSs) in agriculture are becoming increasingly popular, and have begun adopting visualisations to facilitate insights into complex data. However, DSSs for agriculture are often designed as standalone applications, which limits their flexibility and portability. They also rarely provide interactivity, visualise uncertainty and are evaluated with end-users. To address these gaps, we developed six web-based visual-assisted DSSs for various agricultural use cases, including biological efficacy correlation analysis, water stress and irrigation requirement analysis, product price prediction, etc. We then evaluated our DSSs with domain experts, focusing on usability, workload, acceptance and trust. Results showed that our systems were easy to use and understand, and participants perceived them as highly performant, even though they required a slightly high mental demand, temporal demand and effort. We also published the source code of our proposed systems so that they can be re-used or adapted by the agricultural community.

Original languageEnglish
Article number1027
Number of pages30
JournalAgriculture (Switzerland)
Volume12
Issue number7
DOIs
Publication statusPublished - Jul 2022

Keywords

  • data analytics
  • decision support systems
  • interactive visualisations
  • precision agriculture
  • user evaluation

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