Data for PhD Thesis: "Integrating WSN, citizen science, and remote sensing to power a data-driven decision support system for reselient smallholder agriculture"

This thesis focused on building a robust, relibale, accessible, and affordable spatiotemporal data infrastructure to allow continuous data flow from resource-constrained environments to an intelligent decision support system. We integrated IoT-WSN, citizen science, and remote sensing for smallholder farms monitoring. We build agriculture data cube using automated data pipeline and APIs from these sources, which is then used to develop a data-driven knowledge base. The agriculture knowledge base is utilized into a data-driven decision support system using fuzzy logic and association mining models.