Project Description:
EcoWell is a full-stack platform that enables environmental route optimization on the University of Maryland campus through automated ETL pipelines and multi-criteria decision analysis. The system collects raw environmental data from sources such as iNaturalist and admin-uploaded datasets, cleans and structures it using tools like pandas, and stores it in a database for efficient querying and experimentation. Using a weighted linear combination approach, the routing engine generates optimized walking paths that maximize exposure to beneficial environmental factors such as greenery while accounting for user-controlled penalties like distance, time, and route overlap. The platform allows researchers to design experiments by adjusting data layer weights, generate routes based on hypotheses, and evaluate how environmental variables influence perceived wellness. At the same time, everyday users can simply choose their preferences, such as more shade or higher biodiversity, and follow optimized routes across campus designed to enhance their experience. By combining data engineering, geospatial analysis, and user-driven experimentation, EcoWell transforms the campus into a living lab for studying and improving mental well-being through everyday navigation.
