## Inspiration

r.unear.me helps you get exactly where your friends are. In cases when you are supposed to meet them but can't exactly find them, unear.me helps you get to them.

r.unear.me is a webapp that that enables you and your friend to share each other's location on the same page, and the location updates continuously as the people in it move.

## How I built it

You go into the webapp and you get a custom code at the end of url with your location. You can then sent the url to your friends and their location markers will also be added to the page.

## Challenges I ran into

Updating the location coordinates, trying to get firebase, mapbox and azure working together
## Inspiration

We took inspiration from the multitude of apps that help to connect those who are missing to those who are searching for their loved ones and others affected by natural disaster, especially flooding. We wanted to design a product that not only helped to locate those individuals, but also to rescue those in danger. Through the combination of these services, the process of recovering after natural disasters is streamlined and much more efficient than other solutions.

## What it does

Spotted uses a drone to capture and send real-time images of flooded areas. Spotted then extracts human shapes from these images and maps the location of each individual onto a map and assigns each victim a volunteer to cover everyone in need of help. Volunteers can see the location of victims in real time through the mobile or web app and are provided with the best routes for the recovery effort.

## How we built it

The backbone of both our mobile and web applications is HERE.com’s intelligent mapping API. The two APIs that we used were the Interactive Maps API to provide a forward-facing client for volunteers to get an understanding of how an area is affected by flood and the Routing API to connect volunteers to those in need in the most efficient route possible. We also used machine learning and image recognition to identify victims and where they are in relation to the drone. The app was written in java, and the mobile site was written with html, js, and css.

## Challenges we ran into

All of us had a little experience with web development, so we had to learn a lot because we wanted to implement a web app that was similar to the mobile app.

## Accomplishments that we're proud of

Accomplishment: We are most proud that our app can collect and stores data that is available for flood research and provide real-time assignment to volunteers in order to ensure everyone is covered in the shortest time

## What we learned

We learned a great deal about integrating different technologies including XCode, . We also learned a lot about web development and the intertwining of different languages and technologies like html, css, and javascript.

## What's next for Spotted

Future of Spotted: We think the future of Spotted is going to be bright! Certainly, it is tremendously helpful for the users, and at the same time, the program improves its own functionality as data available increases. We might implement a machine learning feature to better utilize the data and predict the situation in target areas. What's more, we believe the accuracy of this prediction function will grow exponentially as data size increases. Another important feature is that we will be developing optimization algorithms to provide a real-time most efficient solution for the volunteers. Other future development might be its involvement with specific charity groups and research groups and work on specific locations outside US.
## Inspiration

Modern meetup apps are too focused on "dating", we wanted to create an app that helps students in the city make new friends on campus. The app gets rid of stalling when it comes to time and place to meet, we implemented a location tracking for each person so that when they match, they can try to meet up immediately.

## What it does

Users can login to the app and fill out the criteria for the person they want to meet within a 1km radius, the app then tries to find a student that matches the criteria. Once found, the students are able to see eachother's locations and can easily meetup by looking at the pin points on the map.

## How we built it

Built using Node.js backend with MongoDB on AWS server, our front-end utilizes javascript uses requests to communicate and gets location data.

## Challenges we ran into

Working with AWS and the Google Maps Javascript API was very hard, Google Maps API was surprisingly hard to work with, the functionalities that they provide is very limited. AWS just had a lot of bugs that we had to work with during setup, once we got past it, working with it was more easier.

## Accomplishments that we're proud of

We were able to get the core functionality of the program to work, sharing location data and seeing other users on the map.