Carbon Footprint Tracker

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  Home screen meant to show a carbon footprint fact of the day with yes or no button field to answer a environmental based question of the day

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  A settings page to manage configurations for the app like notifications, privacy, etc.

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  A details page to display compared user data through machine learning to see the environmental impact of all users on the app

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  Early front end stages

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  Early inspiration

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  User Input Concept for frontend

Inspiration

The inspiration for the Carbon Footprint App came from the growing concern for the environment and the need to reduce our carbon footprint. We wanted to create a tool that would help individuals understand and track their own carbon footprint, as well as offer suggestions on how to reduce it.

What it does

Built with a technology stack based on MongoDB, Express, React Native, NodeJS, and Python, The app allows users to receive a daily notification at a random time, asking a simple yes or no question about an activity that could lead to a carbon footprint. The user is then prompted to provide quantitative data about that activity. The app compares the user's data to the population and provides personalized advice on how to reduce their impact.

How we built it

We engineered the Carbon Footprint App with a stack based on MongoDB, Express, React Native, NodeJS, and Python. React Native was used to build the front end which was managed by Expo and Yarn for package management; it allowed us to create a yes and no response field to answer questions that allowed us to POST data of the client’s carbon footprint pattern. We then developed a machine learning backend through Scikit-Learn on Python to analyze that carbon footprint data and stored it in the MongoDB Atlas Cloud. That MongoDB database is managed through standard CRUD procedures fabricated on PyMongo with Axios, Mongoose, and Express on NodeJS to GET database collection data, prompts, and questions which would then be pushed to the React Native client-side.

Challenges we ran into

Challenges we ran into ranged from technical to inspirational. Technically speaking, we had hardships analyzing user data as it is complicated to compare. We also had the misfortune of struggling with MongoDB Atlas connections with promise rejections during the development stages. Inspirationally speaking, we had to consider what could be possible under the time limit; pivoting for the idea had to occur to adapt to the deadline.

Accomplishments that we're proud of

We are proud to have created an app that helps individuals understand and track their own carbon footprint. We believe that this app can have a positive impact on the environment by encouraging people to be more mindful of the impact they leave on the environment.

What we learned

Our team was working with technology that we were not familiar with such as React Native and Scikit Learn. We also learned how to connect all the tech stack together.

What's next for Carbon Footprint App

Our plan for future is to continue to refine the calculations and add more features to the app such as the ability to track progress over time and integration with other smart devices. Ultimately, our goal is to make the Carbon Footprint Tracker a comprehensive tool for reducing our impact on the environment!

Built With

• css
• expo.io
• express.js
• javascript
• mongodb
• node.js
• post
• python
• react-native
• scikit-learn