## Inspiration

We admired the convenience Honey provides for finding coupon codes. We wanted to apply the same concept except towards making more sustainable purchases online.

## What it does

Recommends sustainable and local business alternatives when shopping online.

## How we built it

Front-end was built with React.js and Bootstrap. The back-end was built with Python, Flask and CockroachDB.

## Challenges we ran into

Difficulties setting up the environment across the team, especially with cross-platform development in the back-end. Extracting the current URL from a webpage was also challenging.

## Accomplishments that we're proud of

Creating a working product!
Successful end-to-end data pipeline.

## What we learned

We learned how to implement a Chrome Extension. Also learned how to deploy to Heroku, and set up/use a database in CockroachDB.

## What's next for Conscious Consumer

First, it's important to expand to make it easier to add local businesses. We want to continue improving the relational algorithm that takes an item on a website, and relates it to a similar local business in the user's area. Finally, we want to replace the ESG rating scraping with a corporate account with rating agencies so we can query ESG data easier.
View the SlideDeck for this project at: [slides](https://docs.google.com/presentation/d/1G1M9v0Vk2-tAhulnirHIsoivKq3WK7E2tx3RZW12Zas/edit?usp=sharing)

## Inspiration / Why

It is no surprise that mental health has been a prevailing issue in modern society. 16.2 million adults in the US and 300 million people in the world have depression according to the World Health Organization. Nearly 50 percent of all people diagnosed with depression are also diagnosed with anxiety. Furthermore, anxiety and depression rates are a rising issue among the teenage and adolescent population. About 20 percent of all teens experience depression before they reach adulthood, and only 30 percent of depressed teens are being treated for it.

To help battle for mental well-being within this space, we created DearAI. Since many teenagers do not actively seek out support for potential mental health issues (either due to financial or personal reasons), we want to find a way to inform teens about their emotions using machine learning and NLP and recommend to them activities designed to improve their well-being.

## Our Product:

To help us achieve this goal, we wanted to create an app that integrated journaling, a great way for users to input and track their emotions over time. Journaling has been shown to reduce stress, improve immune function, boost mood, and strengthen emotional functions. Journaling apps already exist, however, our app performs sentiment analysis on the user entries to help users be aware of and keep track of their emotions over time.

Furthermore, every time a user inputs an entry, we want to recommend the user something that will lighten up their day if they are having a bad day, or something that will keep their day strong if they are having a good day. As a result, if the natural language processing results return a negative sentiment like fear or sadness, we will recommend a variety of prescriptions from meditation, which has shown to decrease anxiety and depression, to cat videos on Youtube. We currently also recommend dining options and can expand these recommendations to other activities such as outdoors activities (i.e. hiking, climbing) or movies.

**We want to improve the mental well-being and lifestyle of our users through machine learning and journaling.This is why we created DearAI.**

## Implementation / How

Research has found that ML/AI can detect the emotions of a user better than the user themself can. As a result, we leveraged the power of IBM Watson’s NLP algorithms to extract the sentiments within a user’s textual journal entries. With the user’s emotions now quantified, DearAI then makes recommendations to either improve or strengthen the user’s current state of mind. The program makes a series of requests to various API endpoints, and we explored many APIs including Yelp, Spotify, OMDb, and Youtube. Their databases have been integrated and this has allowed us to curate the content of the recommendation based on the user’s specific emotion, because not all forms of entertainment are relevant to all emotions.

For example, the detection of sadness could result in recommendations ranging from guided meditation to comedy. Each journal entry is also saved so that users can monitor the development of their emotions over time.

## Future

There are a considerable amount of features that we did not have the opportunity to implement that we believe would have improved the app experience. In the future, we would like to include video and audio recording so that the user can feel more natural speaking their thoughts and also so that we can use computer vision analysis on the video to help us more accurately determine users’ emotions. Also, we would like to integrate a recommendation system via reinforcement learning by having the user input whether our recommendations improved their mood or not, so that we can more accurately prescribe recommendations as well. Lastly, we can also expand the APIs we use to allow for more recommendations.
## Inspiration

Because of covid-19 and the holiday season, we are getting increasingly guilty over the carbon footprint caused by our online shopping. This is not a coincidence, Amazon along contributed over 55.17 million tonnes of CO2 in 2019 alone, the equivalent of 13 coal power plants.

We have seen many carbon footprint calculators that aim to measure individual carbon pollution. However, the pure mass of carbon footprint too abstract and has little meaning to average consumers. After calculating footprints, we would feel guilty about our carbon consumption caused by our lifestyles, and maybe, maybe donate once to offset the guilt inside us.

The problem is, climate change cannot be eliminated by a single contribution because it's a continuous process, so we thought to gamefy carbon footprint to cultivate engagement, encourage donations, and raise awareness over the long term.

## What it does

We build a google chrome extension to track the user’s amazon purchases and determine the carbon footprint of the product using all available variables scraped from the page, including product type, weight, distance, and shipping options in real-time. We set up Google Firebase to store user’s account information and purchase history and created a gaming system to track user progressions, achievements, and pet status in the backend.

## How we built it

We created the front end using React.js, developed our web scraper using javascript to extract amazon information, and Netlify for deploying the website. We developed the back end in Python using Flask, storing our data on Firestore, calculating shipping distance using Google's distance-matrix API, and hosting on Google Cloud Platform. For the user authentication system, we used the SHA-256 hashes and salts to store passwords securely on the cloud.

## Challenges we ran into

This is our first time developing a web app application for most of us because we have our background in Mechatronics Engineering and Computer Engineering.

## Accomplishments that we're proud of

We are very proud that we are able to accomplish an app of this magnitude, as well as its potential impact on social good by reducing Carbon Footprint emission.

## What we learned

We learned about utilizing the google cloud platform, integrating the front end and back end to make a complete webapp.

## What's next for Purrtector

Our mission is to build tools to gamify our fight against climate change, cultivate user engagement, and make it fun to save the world. We see ourselves as a non-profit and we would welcome collaboration from third parties to offer additional perks and discounts to our users for reducing carbon emission by unlocking designated achievements with their pet similar. This would bring in additional incentives towards a carbon-neutral lifetime on top of emotional attachments to their pet.

## Domain.com Link

<https://purrtector.space> Note: We weren't able to register this via domain.com due to the site errors but Sean said we could have this domain considered.