We were thinking about the environmental challenges that the planet faces as the population increases. By considering the tracks that are proposed by this particular hackathon, we thought farming would be an interesting topic to cover since a lot of issues arise within agriculture.
What it does
With our app, we decided to tackle the issue of chemicals and water usage as well as livestock treatment. The overuse of chemicals and water harms the environment, but it can be challenging to forgo using these substances while farming. To encourage a more environmentally conscious farming practice, our web app gives farmers a grade based on the ratio of their crop yield to substance usage. This is done by first asking the farmer what kind of score they would like to generate, chemical or water. If they choose chemical, the farmer will be prompted to enter the amount of crops they were able to generate at the end of the year, the acreage used to grow these crops, and the acreage that was treated with each of the chemical substances. After going through a formula we generated to create the score, the farmer will receive a letter grade depending on where their numerical score fell into. Water score is dependent on the ratio of crop yield to the number of acres that are irrigated. Again, depending on where their score falls into, the farmer will receive the respective letter grade. The cow pasture score measures the farmer's minimization of possible pasture space in order to prevent unnecessary cutting down of trees. It uses a formula for balancing animals with their forage to find the minimum amount of pasture needed, then prompts the farmer for his or her amount of pasture. Based on the difference between the farmer's amount of pasture and the minimum, a letter grade from A to D is outputted.
How we built it
We used Node and the Node Package Manager which gave us CSVToJSON and axios for our data and prompt-sync. We then used ExpressJS for the user interface. The USDA's numerous APIs proved helpful, but we also got data from Kaggle datasets.
Challenges we ran into
At first, we were going to use HTML - just a front-end website that uses API. Soon, we ran into the CORS Policy error which limited our APIs. Then we considered using express.js but that was also a little hard to pickup due to the time constraints, so we switched back to HTML and just create a frontend that helps visualize how we want to format our web app.
The data manipulation also posed its own challenges. Figuring out how to generate the scores and rating system was a little overwhelming because there is so much data available, but we didn't know how to make good use of it. There also wasn't a good source to reference to as a golden standard. We ended up just creating ratios from the data available from the USDA and set that as our standard.
Accomplishments that we're proud of
We are proud of how everything wrapped up. After figuring out the formulas to generate the standard and user scores, our backend successfully took in user input, generate a user score, compare that user score to the standard score, and output a respective grade. Although our frontend is simple not connected to our backend, we like how it turned out.
What we learned
For our backend, we learned how to use NodeJS and its various packages as well as data manipulation of user input and CSV retrieval. We learned express.js and HTML for our frontend.
What's next for FarmaKarma