## Inspiration

Polycystic Ovary Syndrome (PCOS) is a disorder that affects 5-10% of the female population due to an imbalance of hormones. Women that experience PCOS have an increased risk of type 2 diabetes, high blood pressure, high cholesterol, anxiety, and depression. Like a lot of women's disorders, it’s common for PCOS to receive a delayed or no diagnosis at all due to lack of awareness of PCOS symptoms and the wide-range of symptoms. As a consequence, many women unknowingly suffer from the health risks without proper treatment.

We have developed an application for the You.com search engine that compares your health data with information about women's health from your searches, allowing you to monitor your health status and identify potential indicators of PCOS.

## What it does

When you search anything related to women’s sexual and reproductive health, our application pops up with 3 key features: (1) providing comprehensive information on PCOS by web scrapping, (2) comparing these symptoms with information from your health app, (3) donation feature that allows you to contribute to organizations dedicated to providing resources to women with the condition.

## How we built it

Using You.com's Developer Dashboard, we utilized their editor to design the user interface, incorporating two APIs for personalized health data and generalized PCOS information. Furthermore, we integrated checkbook.io to enable donations directly to community organizations just with payee info!

## Challenges we ran into

We encountered challenges while incorporating the API into the You.com codebase, primarily due to the limitations of the "Form" components and difficulties placing components precisely as desired. Additionally, the integration of Checkbook.io was challenging due to the steps involved with user authentication and bank account creation.

## Accomplishments that we're proud of

The donation app tile is fully functional and we can track the donations given by the user through email and the Sandbox environment.

## What we learned

We learned about how to create and integrate APIs, front-end development using You.com, and functionality of HTTP POST and GET methods while deepening our knowledge of PCOS and its impact on women's health.

## What's next for YouCare

We aim to expand this tool to include more topics in women's health like STDs, pregnancy and sex education, each with their unique features to improve awareness. It’s capabilities can further develop to address all queries that deal with women’s health like providing advice on topics related to women's health, like periods or menstrual products. For instance, it can show you a summary of your cycle and suggest products that might be useful for you, and physicians you should consider etc.
## Inspiration

Due to a lot of work and family problems, People often forget to take care of their health and food. Common health problems people know a day's faces are BP, heart problems, and Diabetics. Most people face mental health problems, due to studies, jobs, or any other problems. This Project can help people find out their health problems.
It helps people in easy recycling of items, as they are divided into 12 different classes.
It will help people who do not have any knowledge of plants and predict if the plant is having any diseases or not.

## What it does

On the Garbage page, When we upload an image it classifies which kind of garbage it is. It helps people with easy recycling.
On the mental health page, When we answer some of the questions. It will predict If we are facing some kind of mental health issue.
The Health Page is divided into three parts. One page predicts if you are having heart disease or not. The second page predicts if you are having Diabetics or not. The third page predicts if you are having BP or not.
Covid 19 page classify if you are having covid or not
Plant\_Disease page predicts if a plant is having a disease or not.

## How we built it

I built it using streamlit and OpenCV.

## Challenges we ran into

Deploying the website to Heroku was very difficult because I generally deploy it. Most of this was new to us except for deep learning and ML so it was very difficult overall due to the time restraint. The overall logic and finding out how we should calculate everything was difficult to determine within the time limit. Overall, time was the biggest constraint.

## Accomplishments that we're proud of

## What we learned

Tensorflow, Streamlit, Python, HTML5, CSS3, Opencv, Machine learning, Deep learning, and using different python packages.

## What's next for Arogya
## Inspiration

We have all heard about the nutrition and health issues from those who surround us. Yes, adult obesity has plateaued since 2003, but it's at an extremely high rate. Two out of three U.S. adults are overweight or obese. If we look at diabetes, it's prevalent in 25.9% americans over 65. That's 11.8 million people! Those are the most common instances, let's not forget about people affected by high blood pressure, allergies, digestive or eating disorders—the list goes on. We've created a user friendly platform that utilizes Alexa to help users create healthy recipes tailored to their dietary restrictions. The voice interaction allows for a broad range of ages to learn how to use our platform. On top of that, we provide a hands free environment to ease multitasking and users are more inclined to follow the diet since it’s simple and quick to use.

## How we built it

The backend is built with Flask on Python, with the server containerized and deployed on AWS served over nginx and wsgi. We also built this with scale in mind as this should be able to scale to many millions of users, and by containerizing the server with docker and hosting it on AWS, scaling it horizontally is as easy as scaling it vertically, with a few clicks on the AWS dev console.
The front end is powered by bootstrap and Jinja (JavaScript Framework) that interfaces with a mySQL database on AWS through Flask’s object relational mapping.
All in all, Ramsay is a product built on sweat, pressure, lack of sleep and <3

## Challenges we ran into

The deployment pipeline for alexa is extremely cumbersome due to the fact that alexa has a separate dev console and debugging has to be done on the page. The way lambda handles code change is also extremely inefficient. It has taken a big toll on the development cycle and caused a lot of frustrating debugging times..

It was also very time consuming for us to manually scrape all the recipe and ingredients data from the web, because there no open source recipe API that satisfies our needs. Many of them are either costly or had rate limit restrictions on the endpoints for the free tier, which we are not content with because we wanted to provide a wide range of recipe selection for the user.

Scraping different sites gave us a lot of dirty data that required a lot of work to make it usable. We ended up using NLTK to employ noun and entity extraction to get meaningful data from a sea of garbage.

## Accomplishments that we're proud of

We managed to build out a Alexa/Lambda deployment pipeline that utilizes AWS S3 buckets and sshfs. The local source files are mounted on a remote S3 bucket that syncs with the Lambda server, enabling the developer to skip over the hassle of manually uploading the files to the lambda console everytime there is a change in the codebase.

We also built up a very comprehensive recipe database with over 10000 recipes and 3000 ingredients that allows the user to have tons of selection.

This is also the first Alexa app that we made that has a well thought out user experience and it works surprisingly well. For once Alexa is not super confused every time a user ask a question.

## What we learned:

We learnt how to web scrape implementing NLTK and BeautifulSoup python libraries. This was essential to create of database containing information about ingredients and recipe steps as well. We also became more proficient in using git and SQL. We are now git sergeants and SQL soldiers.

## What's next for Ramsay:

Make up for the sleep that we missed out on over the weekend :')