Date of Award

6-3-2026

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2026

Department

Computer Science and Engineering

First Advisor

Angela Musurlian

Second Advisor

Maia Dedrick

Abstract

This project focused on the continued development of Maya Roots, a mobile and web-based platform designed for farmers in Tahcabo: a rural agricultural community located in Yucatán, Mexico. Yucatán faces unique agricultural challenges due to its karst limestone terrain and highly variable land conditions that can significantly impact farming outcomes. At the same time, traditional agricultural knowledge such as Milpa farming practices is increasingly at risk of being lost across generations. These environmental and cultural challenges highlighted the need for a portable, accessible system that could preserve agricultural knowledge, improve access to geospatial information, and strengthen communication between farmers and experts directly in the field. The previously existing system lacked scalable communication between farmers and experts, an accessible UI, and much of the geospatial data collected about the region was unusable to the people actually living and farming there. In response, we expanded the Maya Roots system to be more scalable and accessible through the integration of LiDAR visualization, an improved reporting workflow, a connected Admin Dashboard, multilingual support, and accessibility-focused design.

Our final Maya Roots system provides a scalable feedback loop between farmers and experts, portable access to LiDAR-based terrain information, and culturally relevant educational content through Agricultural Cycles, weather, and lunar cycle modules. However, limitations still remain, particularly regarding production-level security, administrative tooling, and long-term content management. Future work includes implementing stronger authentication and role-based access for the Admin Dashboard, improving CRUD functionality so administrators may dynamically manage educational and map content, and expanding offline and geospatial capabilities. Ultimately, Maya Roots demonstrated how community-centered engineering can empower users by returning valuable agricultural and geospatial knowledge to the people it originates from, making that information more accessible, understandable, and usable while respecting the culture and land it is built upon.

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