**Made by Ella Smith (ella#4637) & Akram Hannoufa (ak\_hannou#7596) -- Team #15**

*Domain: <https://www.birtha.online/>*

## Inspiration

Conversations with friends and family about the difficulty of finding the right birth control pill on the first try.

## What it does

Determines the brand of hormonal contraceptive pill most likely to work for you using data gathered from drugs.com. Data includes: User Reviews, Drug Interactions, and Drug Effectiveness.

## How we built it

The front-end was built using HTML, CSS, JS, and Bootstrap. The data was scraped from drugs.com using Beautiful Soup web-scraper.

## Challenges we ran into

Having no experience in web-dev made this a particularly interesting learning experience. Determining how we would connect the scraped data to the front-end was challenging, as well as building a fully functional multi-page form proved to be difficult.

## Accomplishments that we're proud of

We are proud of the UI design, given it is our first attempt at web development. We are also proud of setting up a logic system that provides variability in the generated results. Additionally, figuring out how to web scrape was very rewarding.

## What we learned

We learned how to use version control software, specifically Git and GitHub. We also learned the basics of Bootstrap and developing a functional front-end using HTML, CSS, and JS.

## What's next for birtha

Giving more detailed and accurate results to the user by further parsing and analyzing the written user reviews. We would also like to add some more data sources to give even more complete results to the user.
### 🌟 Inspiration

We're inspired by the idea that emotions run deeper than a simple 'sad' or 'uplifting.' Our project was born from the realization that personalization is the key to managing emotional states effectively.

### 🤯🔍 What it does?

Our solution is an innovative platform that harnesses the power of AI and emotion recognition to create personalized Spotify playlists. It begins by analyzing a user's emotions, both from facial expressions and text input, to understand their current state of mind. We then use this emotional data, along with the user's music preferences, to curate a Spotify playlist that's tailored to their unique emotional needs.

What sets our solution apart is its ability to go beyond simplistic mood categorizations like 'happy' or 'sad.' We understand that emotions are nuanced, and our deep-thought algorithms ensure that the playlist doesn't worsen the user's emotional state but, rather, optimizes it. This means the music is not just a random collection; it's a therapeutic selection that can help users manage their emotions more effectively.

It's music therapy reimagined for the digital age, offering a new and more profound dimension in emotional support.

### 💡🛠💎 How we built it?

We crafted our project by combining advanced technologies and teamwork. We used Flask, Python, React, and TypeScript for the backend and frontend, alongside the Spotify and OpenAI APIs.

Our biggest challenge was integrating the Spotify API. When we faced issues with an existing wrapper, we created a custom solution to overcome the hurdle.

Throughout the process, our close collaboration allowed us to seamlessly blend emotion recognition, music curation, and user-friendly design, resulting in a platform that enhances emotional well-being through personalized music.

### 🧩🤔💡 Challenges we ran into

🔌 API Integration Complexities: We grappled with integrating and harmonizing multiple APIs.

🎭 Emotion Recognition Precision: Achieving high accuracy in emotion recognition was demanding.

📚 Algorithm Development: Crafting deep-thought algorithms required continuous refinement.

🌐 Cross-Platform Compatibility: Ensuring seamless functionality across devices was a technical challenge.

🔑 Custom Authorization Wrapper: Building a custom solution for Spotify API's authorization proved to be a major hurdle.

### 🏆🥇🎉 Accomplishments that we're proud of

#### Competition Win: 🥇

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Our victory validates the effectiveness of our innovative project.

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#### Functional Success: ✔️

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The platform works seamlessly, delivering on its promise.

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#### Overcoming Challenges: 🚀

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Resilience in tackling API complexities and refining algorithms.

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#### Cross-Platform Success: 🌐

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Ensured a consistent experience across diverse devices.

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#### Innovative Solutions: 🚧

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Developed custom solutions, showcasing adaptability.

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#### Positive User Impact: 🌟

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Affirmed our platform's genuine enhancement of emotional well-being.

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### 🧐📈🔎 What we learned

🛠 Tech Skills: We deepened our technical proficiency.

🤝 Teamwork: Collaboration and communication were key.

🚧 Problem Solving: Challenges pushed us to find innovative solutions.

🌟 User Focus: User feedback guided our development.

🚀 Innovation: We embraced creative thinking.

🌐 Global Impact: Technology can positively impact lives worldwide.

### 🌟👥🚀 What's next for Look 'n Listen

🚀 Scaling Up: Making our platform accessible to more users.

🔄 User Feedback: Continuous improvement based on user input.

🧠 Advanced AI: Integrating more advanced AI for better emotion understanding.

🎵 Enhanced Personalization: Tailoring the music therapy experience even more.

🤝 Partnerships: Collaborating with mental health professionals.

💻 Accessibility: Extending our platform to various devices and platforms.
## Inspiration

Our inspiration is based on hearing from industry colleagues that they often need to do research to keep up with the new research occurring in their domain. Research materials are often spread across multiple different sites and require users to actively search through information.

## What it does

We have created a web application that scrapes RSS feeds from the web and consolidates the information.

## How we built it

For our backend we are using google cloud Postgres storage, as well as pythonFastApi; and our front end uses react and a CSS framework called bulma.

## Challenges we ran into

We ran into some challenges with integrating with the database

## Accomplishments that we're proud of

We are proud of the various moving pieces coming together from the backend to the front end.

## What we learned

We learned about various different tools to help with development as well as the value of working in a team to debug/ troubleshoot issues.

## What's next for nuResearch

For the future, we also plan to use Twillio Sendgrid to send out email notifications to subscribers.