- 2nd Place Winning Certificate located here!
Agriculturists require information to make the correct decisions. In order to increase the accessibility to high-level datasets from NASA and other agencies, we made "Project Soil Tycoon." For example, if a researcher wants to know the most prominent fruit to plant on its soil to have the greatest annual return, the application will scrape the internet to select a relevant dataset publicly available on the internet, extract relevant features from this dataset, and finally enable the user to visualize and compare the yield of this fruit. These agriculturists must have reliable projections to drive their insights. This is important because a data platform should not be the deciding factor whether food is effectively produced at small-holder farmer levels. Food security depends on it.
Soil Tycoon is a familiar interface to many, it's modern. Existing platforms are great if you live, eat, breath data. However, the experience is frustrating at best for your typical user. Humans can only make decisions given what information they know. Why should important information, such as climate and food data for the agriculturist, be obtainable only by those fluent in data science? Beginning by mimicking a search engine, a user can search by familiar terms to come upon results. By abstracting away pieces not immediately necessary, and a minimal user interface, only the info you need is there. There is no monstrous list of unfamiliar abbreviations, metadata, or mentions of equipment.
Coding languages:
VSC
Python
Flask
S3
Google Big Query
HTML
CSS
Tools used:
Figma
Adobe Illustrator
Adobe After Effects
Tableau
render.com
As of our prototype, we haven't implemented artificial intelligence. However, it's in the pipeline. We determined that natural language, semantic analysis of datasets could make sorting through untold results easier and faster. That would be confirmed or otherwise in prototyping and user research/feedback. The Cameroonionauts collectively have decided to go lightweight first without immediately tacking on a new layer.
NASA EARTHData USDA AG Data Commons USDA AG Data Commons USDA ERS