If we take a moment to stop and think of those who can't speak or hear, we will realize and be thankful for what we have. To make the lives of these differently ables people, we needed to come up with a solution and here we present you with Proximity.

Proximity uses the Myo armband for sign recognition and an active voice for speech recognition. The armband is trained on a ML model reads the signs made by human hands and interprets them, thereby, helping the speech impaired to share their ideas and communicate with people and digital assistants alike. The service is also for those who are hearing impaired, so that they can know when somebody is calling their name or giving them a task.

We're proud of successfully recognizing a few gestures and setting up a web app that understands and learns the name of a person. Apart from that we have calibrated a to-do list that can enable the hearing impaired people to actively note down tasks assigned to them.

We learned an entirely new language, Lua to set up and use the Myo Armband SDK. Apart from that we used vast array of languages, scripts, APIs, and products for different parts of the product including Python, C++, Lua, Js, NodeJs, HTML, CSS, the Azure Machine Learning Studio, and Google Firebase.

We look forward to explore the unlimited opportunities with Proximity. From training it to recognize the entire American Sign Language using the powerful computing capabilities of the Azure Machine Learning Studio to advancing our speech recognition app for it to understand more complex conversations. Proximity should integrate seamlessly into the lives of the differently abled.
## Inspiration

An individual living in Canada wastes approximately 183 kilograms of solid food per year. This equates to $35 billion worth of food. A study that asked why so much food is wasted illustrated that about 57% thought that their food goes bad too quickly, while another 44% of people say the food is past the expiration date.

## What it does

LetsEat is an assistant that comprises of the server, app and the google home mini that reminds users of food that is going to expire soon and encourages them to cook it in a meal before it goes bad.

## How we built it

We used a variety of leading technologies including firebase for database and cloud functions and Google Assistant API with Dialogueflow. On the mobile side, we have the system of effortlessly uploading the receipts using Microsoft cognitive services optical character recognition (OCR). The Android app is writen using RxKotlin, RxAndroid, Retrofit on a MVP architecture.

## Challenges we ran into

One of the biggest challenges that we ran into was fleshing out our idea. Every time we thought we solved an issue in our concept, another one appeared. We iterated over our system design, app design, Google Action conversation design, integration design, over and over again for around 6 hours into the event. During development, we faced the learning curve of Firebase Cloud Functions, setting up Google Actions using DialogueFlow, and setting up socket connections.

## What we learned

We learned a lot more about how voice user interaction design worked.
## Inspiration

Maria, 34, lives in Peru. She feels ill and when she goes to a hospital they schedule her an appointment to see her within 60 days. She had previously waited an average of 40 days to get an appointment, but with Covid-19 the deferral time increased by 50%. She decides to go to a pharmacy to buy drugs, but the diagnosis is often wrong. Like her, millions of people in Latin America and the world do not receive immediate attention, or even if they do, they may have a wrong diagnosis.

## What it does

Zolidarity is a bot based on OpenAI GPT-3. The user provides information about their symptoms and the bot suggests a diagnosis and possible treatment that doctors could perform.

## How we built it

It has been built using the Chat functionality of GPT-3, in which content about different cases is sent, with the patient's symptoms, and the bot responds to a possible diagnosis.

## Challenges we ran into

Time restriction. My initial idea was related to the health sector but it was very different, however after the OpenAI workshop I saw the potential to help patients to have a more accurate diagnosis. As the only member of the team it was difficult to build all the functionality, but I focus more in the testing on OpenAI GPT-3

## Accomplishments that we're proud of

Learn to handle the functionalities of GPT-3 and see the many possibilities of use. This is very exciting.

## What we learned

I learned a lot about various tools (React, Firebase, etc) that can be used to build solutions quickly

## What's next for Zolidarity

Deepen my learning of the tools and build the application.