# Confidence AI !!

## Inspiration

Confidence AI is inspired by the need to help individuals overcome performance anxiety during presentations. Public speaking can be a daunting task, and many people struggle with confidence and delivery. We wanted to create a tool that provides real-time feedback and helps users improve their presentation skills.

## What it does

Confidence AI is a wellness application designed to enhance public speaking skills. It captures live voice and video during presentations and provides instant feedback on performance. The app analyzes vocal tone, facial expressions, and body language to offer insights and suggestions for improvement. Users receive a detailed breakdown of their performance, including the top emotions detected and actionable advice on how to enhance their presentation skills.

## How we built it?

We built Confidence AI using a combination of modern technologies and tools:

* Frontend: HTML, CSS, and JavaScript for the user interface.
* Backend: Python and FastAPI for handling real-time data processing & feedback generation.
* HUME API: Used Empathic Voice Interface API and Expression Measurement API.
* Groq API: To summarize emotions and generate feedback.
* Streaming: WebSockets for live video and voice streaming to capture presentations in real-time.

## Challenges we ran into

* Real-Time Analysis: Ensuring the emotion detection models could process data in real-time without significant lag.
* Accuracy: Training models to accurately detect and interpret emotions from both voice and video inputs.
* User Experience: Designing an intuitive and user-friendly interface that provides clear and actionable feedback without overwhelming the user.

## Accomplishments that we're proud of

* Successfully integrating real-time voice and video analysis into the app.
* Developing highly accurate emotion detection models.
* Creating a seamless and user-friendly interface that helps users improve their presentation skills
 effectively.

## What did we learn?

* The importance of real-time feedback in improving public speaking skills.
* Techniques for effectively training emotion detection models using voice and video data.
* Best practices for designing intuitive user interfaces for wellness applications.

## What's next for Confidence AI?

* Feature Expansion: Adding more advanced analytics and feedback mechanisms.
* Mobile App: Developing a mobile version of the app for greater accessibility.
* User Testing: Conducting extensive user testing to gather feedback and improve the app further.
* Partnerships: Collaborating with public speaking coaches and organizations to enhance the app’s offerings.
## Inspiration

As someone who's been interested in Virology for a *very* long time, I was inspired to make this project based on my own interests

## What it does

This program is predicated on multiple adults going out on an expidition, where a certain number of people are infected with a virus (potency to be decided by the user). The program will arrange and sort the health and susceptability of the individuals, and will have the most susceptable treated by a set number of surgeons, and some treated by (less-skilled) general practitioners

## How we built it

We used a class hierarchy of multiple classes. Every individual is an adult. Some adults are patients. Some adults are doctors. Some doctors are surgeons. Through their abilities and methodology, we were able to simulate (with a +/- 5% accuracy from our calculated expected values) what would actually occur in such an event

## Challenges we ran into

Since my teammates chose to depart from pennapps right after we completed the pseudocode, it was challenging for me to meet the deadline and produce a high-quality program (although I do believe that I succeeded). In fact, as of right now, there's less than 4 minutes left to submit!

## Accomplishments that we're proud of

The calculated accuracy of the project

## What's next for Infection Simulator

We just need a virus to test this program on -- oh wait.
## Inspiration

Travel planning is a pain. Even after you find the places you want to visit, you still need to find out when they're open, how far away they are from one another, and work within your budget. With Wander, automatically create an itinerary based on your preferences – just pick where you want to go, and we'll handle the rest for you.

## What it does

Wander shows you the top destinations, events, and eats wherever your travels take you, with your preferences, budget, and transportation in mind. For each day of your trip, Wander creates a schedule for you with a selection of places to visit, lunch, and dinner. It plans around your meals, open hours, event times, and destination proximity to make each day run as smoothly as possible.

## How we built it

We built the backend on Node.js and Express which uses the Foursquare API to find relevant food and travel destinations and schedules the itinerary based on the event type, calculated distances, and open hours. The native iOS client is built in Swift.

## Challenges we ran into

We had a hard time finding all the event data that we wanted in one place. In addition, we found it challenging to sync the information between the backend and the client.

## Accomplishments that we're proud of

We’re really proud of our mascot, Little Bloop, and the overall design of our app – we worked hard to make the user experience as smooth as possible. We’re also proud of the way our team worked together (even in the early hours of the morning!), and we really believe that Wander can change the way we travel.

## What we learned

It was surprising to discover that there were so many ways to build off of our original idea for Wander and make it more useful for travelers. After laying the technical foundation for Wander, we kept brainstorming new ways that we could make the itinerary scheduler even more useful, and thinking of more that we could account for – for instance, how open hours of venues could affect the itinerary. We also learned a lot about the importance of design and finding the best user flow in the context of traveling and being mobile.

## What's next for Wander

We would love to continue working on Wander, iterating on the user flow to craft the friendliest end experience while optimizing the algorithms for creating itineraries and generating better destination suggestions.