## Inspiration

People are increasingly aware of climate change but lack actionable steps. Everything in life has a carbon cost, but it's difficult to understand, measure, and mitigate. Information about carbon footprints of products is often inaccessible for the average consumer, and alternatives are time consuming to research and find.

## What it does

With GreenWise, you can link email or upload receipts to analyze your purchases and suggest products with lower carbon footprints. By tracking your carbon usage, it helps you understand and improve your environmental impact. It provides detailed insights, recommends sustainable alternatives, and facilitates informed choices.

## How we built it

We started by building a tool that utilizes computer vision to read information off of a receipt, an API to gather information about the products, and finally ChatGPT API to categorize each of the products. We also set up an alternative form of gathering information in which the user forwards digital receipts to a unique email.

Once we finished the process of getting information into storage, we built a web scraper to gather the carbon footprints of thousands of items for sale in American stores, and built a database that contains these, along with AI-vectorized form of the product's description.

Vectorizing the product titles allowed us to quickly judge the linguistic similarity of two products by doing a quick mathematical operation. We utilized this to make the application compare each product against the database, identifying products that are highly similar with a reduced carbon output.

This web application was built with a Python Flask backend and Bootstrap for the frontend, and we utilize ChromaDB, a vector database that allowed us to efficiently query through vectorized data.

## Accomplishments that we're proud of

In 24 hours, we built a fully functional web application that uses real data to provide real actionable insights that allow users to reduce their carbon footprint

## What's next for GreenWise

We'll be expanding e-receipt integration to support more payment processors, making the app seamless for everyone, and forging partnerships with companies to promote eco-friendly products and services to our consumers

[Join the waitlist for GreenWise!](https://dea15e7b.sibforms.com/serve/MUIFAK0jCI1y3xTZjQJtHyTwScsgr4HDzPffD9ChU5vseLTmKcygfzpBHo9k0w0nmwJUdzVs7lLEamSJw6p1ACs1ShDU0u4BFVHjriKyheBu65k_ruajP85fpkxSqlBW2LqXqlPr24Cr0s3sVzB2yVPzClq3PoTVAhh_V3I28BIZslZRP-piPn0LD8yqMpB6nAsXhuHSOXt8qRQY)
## Inspiration

Ethiscan was inspired by a fellow member of our Computer Science club here at Chapman who was looking for a way to drive social change and promote ethical consumerism.

## What it does

Ethiscan reads a barcode from a product and looks up the manufacturer and information about the company to provide consumers with information about the product they are buying and how the company impacts the environment and society as a whole. The information includes the parent company of the product, general information about the parent company, articles related to the company, and an Ethics Score between 0 and 100 giving a general idea of the nature of the company. This Ethics Score is created by using Sentiment Analysis on Web Scraped news articles, social media posts, and general information relating to the ethical nature of the company.

## How we built it

Our program is two parts. We built an android application using Android Studio which takes images of a barcode on a product and send that to our server. Our server processes the UPC (Universal Product Code) unique to each barcode and uses a sentiment analysis neural network and web scraping to populate the android client with relevant information related to the product's parent company and ethical information.

## Challenges we ran into

Android apps are significantly harder to develop than expected, especially when nobody on your team has any experience. Alongside this we ran into significant issues finding databases of product codes, parent/subsidiary relations, and relevant sentiment data.

The Android App development process was significantly more challenging than we anticipated. It took a lot of time and effort to create functioning parts of our application. Along with that, web scraping and sentiment analysis are precise and diligent tasks to accomplish. Given the time restraint, the accuracy of the Ethics Score is not as accurate as possible. Finally, not all barcodes will return accurate results simply due to the lack of relevant information online about the ethical actions of companies related to products.

## Accomplishments that we're proud of

We managed to load the computer vision into our original android app to read barcodes on a Pixel 6, proving we had a successful proof of concept app. While our scope was ambitious, we were able to successfully show that the server-side sentiment analysis and web scraping was a legitimate approach to solving our problem, as we've completed the production of a REST API which receives a barcode UPC and returns relevant information about the company of the product. We're also proud of how we were able to quickly turn around and change out full development stack in a few hours.

## What we learned

We have learned a great deal about the fullstack development process. There is a lot of work that needs to go into making a working Android application as well as a full REST API to deliver information from the server side. These are extremely valuable skills that can surely be put to use in the future.

## What's next for Ethiscan

We hope to transition from the web service to a full android app and possibly iOS app as well. We also hope to vastly improve the way we lookup companies and gather consumer scores alongside how we present the information.
Imagine a world where every time you made a purchase, you could feel like a hero for the planet. A place where you could easily find products that align with your values and make a positive impact on the environment. This is the world our project envisions and is striving to create.
In today's fast-paced world, where convenience and speed reign supreme, it's easy to forget about the impact our actions have on the environment. But what if every time we made a purchase, we could do our part to protect the planet? That's exactly what our project aims to do.

Our website is a one-stop shop for consumers looking to make eco-friendly purchases. By categorizing products based on their carbon footprint, we make it easy for users to choose the most sustainable option. Products with the lowest carbon footprint are represented by the color green, while those with medium and high carbon footprints are represented by orange and red respectively.

But our project doesn't stop at just providing information. We also incentivize users to make sustainable choices by offering a unique reward for purchases made through our website. After a product is purchased, customers will receive a code to enter on our website, which will unlock a special NFT (non-fungible token) as a reward. These NFTs can be shared on social media, allowing users to boast about their eco-friendly choices and encouraging their friends to do the same.

One of the major challenges we faced was utilizing different APIs in one project. We had to integrate various APIs such as Verbwire and OpenAI to provide accurate carbon footprint data and also to sync them together seamlessly. Despite the obstacles, we were able to overcome them and are now proud to offer a platform that makes it easy and rewarding for consumers to make such eco-friendly choices.

We believe that this element of virality is what will make our project truly successful. By making it easy and rewarding to make sustainable purchases, we hope to inspire a movement of environmentally conscious consumers, who will collectively make a significant impact on the fight against climate change.