Descripción:

Smart agriculture is an active research field. Currently, many researchers are working on the construction of platforms directed to improve efficiency, crop processes, and data awareness. However, it is common that developers focus on data monitoring instead of the data relevance for decision making or the costs associated with the creation of monitoring platforms. In this paper, we present a classification of the data required by researchers on the construction of decision-support systems applied to smart agriculture processes. By using this classification, the user can define which data are relevant according to the characteristics of the problem that needs to be solved.We have applied the classification to data recollected in a study case conducted by the end of last year. Besides, we identify a list of agronomic and climatic variables commonly used in the construction of decision support systems. We apply the classification to this list of variables as an example for researchers. As a conclusion, this typification permits the researcher to identify data that has to be monitored and controlled, and data that does not have to be measured, the later based on the data characteristics and utility for the farmer.

Tipo de publicación: Conference Paper

Publicado en: 2019 IV Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

Descripción:

Technological solutions for smart agriculture are essential for enhancing decision-making, especially for small-scale farmers with limited technological proficiency. This study evaluates a data visualization system designed for smart agriculture, focusing on its usability, utility, and user experience. The evaluation involved diverse participants, including farmers and students from the Agronomy, Physics, and Computing disciplines, using standardized questionnaires like the System Usability Scale (SUS) and the User Experience Questionnaire (UEQ). The results indicate strong acceptance and interest in the system, with users appreciating its innovative elements, such as speedometer-style charts and colour-coded thresholds. These visualizations address the limitations of traditional agricultural tools by providing clearer decision-making guidance. This research offers practical insights into designing user-friendly data visualization tools for small-scale farmers. It underscores the importance of intuitive, user-centred visualizations in improving agricultural productivity and provides a foundation for future studies in precision agriculture. The findings highlight the potential of such systems to bridge the gap between complex data and actionable insights, particularly for users with varying levels of technological familiarity.

Tipo de publicación: Conference Paper

Publicado en: Advanced Research in Technologies, Information, Innovation and Sustainability