## Inspiration

One of the biggest socio-economic challenges that the world is encountering and least talked about is the aging population and how the divide between the older and younger generation could potentially disrupt societies (issues like Brexit, 'OK Boomer', increase in elderly crime rate in South Korea, etc.). Unlike in the past, with improved healthcare, the populations in most developed countries enjoy longer life expectancy with healthier lifestyles. As a consequence, the older population have a lot of value to offer to the younger generation. According to a survey conducted in Feb 2017 in the US, 77% of the adults are willing to engage with the younger generation in building meaningful intergenerational relationships.

## What it does

This is an app to connect youth and seniors to build meaningful intergenerational relationships to foster an engaged community. The users can express their preferences and match appropriately with their counterparts. They can use the in-house messaging service and plan meet-ups.

## How we built it

We primarily used python, flask, html and css to build this app. We built the app using python and flask. Azure was used to connect a database to the app so as to store the user information.

## Challenges we ran into

* Learning how to use Azure for SQL database and Web App Deployment
* Connecting a database to the app.
* Problem shooting & Debugging Issues related to ODBC driver
* Incorporate html elements with minimal/no-background.
* Utilising Flask for simulated user-login journey
* Segregating Pages depending on verified authentification.

## Accomplishments that we're proud of

We are proud of the fruition from ideation in the past 20 hours to build a basic product to serve a purpose that the society could benefit from. We learnt a lot not just from this idea, but also from the other countless ideas that were genereated during our team's 6 hour brain storming our team endured.

## What's next for YES (Youth Engaging Seniors)

* Better improve the app UI, which was primarily limited by our HTML and Flask familiarity. For a better visualisation of our app, please refer to the App Mock-up in the provided Figma sketch.
* The next step would be to incorporate an incentive based mentorship program which could be sponsored by governments to provide subsidized travel, project grants, tuition fee credits, etc.
* Allow a beta deployment and get some feedback from users.
* Pitch this idea to investors to scale up the same.
## Inspiration

Going home for winter break and seeing friends was a great time, but throughout all the banter, I realized that our conversations often took a darker turn, and I worried for my friends' mental health. During the school year, it was a busy time and I wasn't able to stay in touch with my friends as well as I had wanted to. After this realization, I also began to question my own mental health - was I neglecting my health?

We were inspired to build a web app that would increase awareness about how friends were doing mentally that could also provide analytics for ourselves. We thought there was good potential in text due to the massive volumes of digital communication and how digital messages can often reveal some the that may be hidden in everyday communication.

## What it does

It parses user text input into a sentiment score, using Microsoft Azure, where 0 is very negative and 1 is very positive. Over a day, it averages the input for a specific user and logs the text files. Friends of the user can view the weekly emoji graphs, and receive a text message if it seems like the user is going through a rough spot and needs someone to talk to.

We also have an emoji map for displaying sentiments of senders around the world, allowing us to see events that invoke emotional responses in a particular area. We hope that this is useful data for increased global and cultural awareness.

## How we built it

We used React.js for the front-end and used Flask with Python for the backend. We used Azure for the sentiment analysis and Twillio to send text messages.

## Challenges we ran into

One of the biggest bottlenecks was connecting our front-end and back-end. Additionally, we had security concerns regarding cross origin resource sharing that made it much more difficult to interface with all the different databases. We had too many APIs that we wanted to connect that made things difficult too.

## Accomplishments that we're proud of

We were able to create a full-stack app web app on our own, despite the challenges. Some of the members of the team had never worked on front-end before and it was a great, fun experience learning how to use JS, Flask, and HTML.

## What we learned

We learned about full stack web app development and the different languages required. We also became more aware of the moving parts behind a web app, how they communicate with each other, and the challenges associated with that.

## What's next for ment.ally

Our original idea was actually a Chrome extension that could detect emotionally charged messages the user types in real-time and offer alternatives in an attempt to reduce miscommunication potentially hurtful to both sides. We would like to build off of our existing sentiment analysis capabilities to do this. Our next step would be to set up a way to parse what the user is typing and underline any overly strong phrases (similar to how Word underlines misspelt words in red). Then we could set up a database that maps some common emotionally charged phrases with some milder ones and offers those as suggestions, possibly along with the reason (e.g. "words in this sentence can trigger feelings of anger!).
## Inspiration

One of our team members, Andy, ended up pushing back his flu shot as a result of the lengthy wait time and large patient count. Unsurprisingly, he later caught the flu and struggled with his health for just over a week. Although we joke about it now, the reality is many medical processes are still run off outdated technology and can easily be streamlined or made more efficient. This is what we aimed to do with our project.

## What it does

Streamlines the process of filling out influenza vaccine forms for both medical staff, as well as patients.
Makes the entire process more accessible for a plethora of demographics without sacrificing productivity.

## How we built it

Front-End built in HTML/CSS/Vanilla JavaScript (ES6)
Back-End built with Python and a Flask Server.
MongoDB for database.
Microsoft Azure Vision API, Google Cloud Platform NLP for interactivity.

## Challenges we ran into

Getting Azure's Vision API to get quality captures to be able to successfully pull the meaningful data we wanted.
Front-End to Back-End communication with GCP NLP functions triggering events.

## Accomplishments that we're proud of

Successfully implementing cloud technologies and tools we had little/no experience utilizing, coming into UofTHacks.
The entire project overall.

## What we learned

How to communicate image data via webcam and Microsoft Azure's Vision AP and analyze Optical Character Recognition results.
Quite a bit about NLP tendencies and how to get the most accurate/intended results when utilizing it.
Github Pages cannot deploy Flask servers LOL.
How to deploy with Heroku (as a result of our failure with Github Pages).

## What's next for noFluenza

Payment system for patients depending on insurance coverage
Translation into different languages.