Fertility Prediction Model

Home Page with Navigation Bar
Second part of home page

Inspiration

I went on a walk outside and I noticed different patches of land. One patch of land just so happens to be dry and dusty and another patch of land is moist and muddy. By looking at the land, I begin to ponder of the impacts of lands that are both dry and dusty AND moist and muddy across the world and how they affect the habitat of civilians and wildlife. I was also reminded by the "Fertile Crescent" which kickstarted the transition of humans from the tribal hunter-gatherer lifestyles to a lifestyle based off of agriculture and cultivation of crops. This further empowered me to understand the correlation of climate and weather between fertile, nutrient-dense land sustainable for farming and any major cultivations required. Thus introduced the "Fertility Prediction Model", where predictions on fertility over the land were made.

What it does

The fertility prediction model assesses and predicts trends in fertility over a selected country. The fertility prediction model evaluates the level of fertility based on soil quality, climate and the rainfall distribution of the land. Once the fertility prediction model makes it's assessment, then the fertility prediction model will provide solutions for future generations and possibly future governments so that they can take the most appropriate action.

How we built it

The production of this web application was full-stack as it integrated both front-end and back-end principles. For front-end, the React library of JavaScript as well as JSX and CSS were used in the development and styling of the website template. For back-end, Express.js and Docker were used to handle front-end code and changes made to the front-end code through user input. We also added the Hugging Face library in JavaScript to produce preventative solutions towards helping an area maintain it's current fertility. To store, retrieve and manipulate data, MySQL was used with both the front-end and the back-end code. As for managing different versions and collaborating on code seamlessly, the Git tool was used to push and pull changes made to and from the GitHub repository (respectively).

Challenges we ran into

There were a lot of challenges in particular that we ran into, such as:

Looking for different categories of data from different websites
Accidental deletion of crucial files (luckily Git was used)
Overlap of images and text in the website for different screen sizes
Misalignment of JSON files in the main source folder of the repository.

Accomplishments that we're proud of

Despite the challenges we've faced there were also some accomplishments that we were proud of, such as:

Success in communication between front-end and back-end code
Success in configuring databases and seamlessly using it with back-end code
Successfully predicting changes in fertility, climate and rainfall through multi-linear equations and then displaying the information through line charts.
The layout and animation of the website through React.
The use of Generative AI through Hugging Face to produce a preventative solution towards helping an area maintain it's current fertility.

What we learned

Upon competing in this hackathon there were several interesting lessons which helped all of us build a greater dossier of skills, more specifically we learned about React and Express.js and how they serve as a powerful library and framework, respectively, for web development. We also learned about important tools to handle code and data such as MySQL, Git and Docker.

Besides technical skills with real tools to help us develop this powerful web application we also learned about skills related to working in a team, such as communication, collaboration and leadership. Those 3 qualities that exist in everyone in a group will further enhance team chemistry and will also serve as foundational personality blocks

What's next for Fertility Prediction Model

We hope to improve our skills in React, Express, MySQL, Docker and Git to develop an even more powerful fertility prediction model that is supported on any device possible not only through layout but through computational power used as well.

Built With

Submitted to

TerraHacks

Created by

I worked on creating the slides with my teammate, Suhail, collaborated with my another teammate, Amitoz to figure out the soil types and work with SQL, worked with Hieue to solve the equations

Fahad Bin Rahman
As someone who worked on the front-end, I was responsible for designing the main layout of the page, navbar and images through the use of React and CSS. Although it was my first time understanding the syntax of React, with the help of my teammates I successfully laid down the foundation to design a modernistic and environmentally-themed website.

Suhail Moeen
My main contribution was the vision of what data to use and how we could compute predictions. After that, I researched the indicator datasets and helped integrate them into MySQL by optimizing the CSV into a .sql file. I also worked on integrating Generative AI into solving the Solutions page of the front end. I also produced the React Js and the CSS on the Solutions page. I also assisted with the CSS for the front and ensured that all pages were set up properly. I also ensured that correct calculations were being conducted in the backend and advised how the entire model should be conducted.

Amitoz Banga
I focused primarily on backend development, creating Dockerfiles and Docker Compose configurations to streamline the deployment process. I ensured the database was cleaned up and integrated communication between the frontend and backend, as well as between the backend and the database. Additionally, I completed the development of the Model page, including the interacting map and the data visualization, for both the frontend and backend.

Hieu Nguyen

Updates

Suhail Moeen started this project — Aug 04, 2024 08:57 AM EDT

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