## Inspiration

GeoGuesser is a fun game which went viral in the middle of the pandemic, but after having played for a long time, it started feeling tedious and boring. Our Discord bot tries to freshen up the stale air by providing a playlist of iconic locations in addendum to exciting trivia like movies and monuments for that extra hit of dopamine when you get the right answers!

## What it does

The bot provides you with playlist options, currently restricted to Capital Cities of the World, Horror Movie Locations, and Landmarks of the World. After selecting a playlist, five random locations are chosen from a list of curated locations. You are then provided a picture from which you have to guess the location and the bit of trivia associated with the location, like the name of the movie from which
we selected the location. You get points for how close you are to the location and if you got the bit of trivia correct or not.

## How we built it

We used the *discord.py* library for actually coding the bot and interfacing it with discord. We stored our playlist data in external *excel* sheets which we parsed through as required. We utilized the *google-streetview* and *googlemaps* python libraries for accessing the google maps streetview APIs.

## Challenges we ran into

For initially storing the data, we thought to use a playlist class while storing the playlist data as an array of playlist objects, but instead used excel for easier storage and updating. We also had some problems with the Google Maps Static Streetview API in the beginning, but they were mostly syntax and understanding issues which were overcome soon.

## Accomplishments that we're proud of

Getting the Discord bot working and sending images from the API for the first time gave us an incredible feeling of satisfaction, as did implementing the input/output flows. Our points calculation system based on the Haversine Formula for Distances on Spheres was also an accomplishment we're proud of.

## What we learned

We learned better syntax and practices for writing Python code. We learnt how to use the Google Cloud Platform and Streetview API. Some of the libraries we delved deeper into were Pandas and pandasql. We also learned a thing or two about Human Computer Interaction as designing an interface for gameplay was rather interesting on Discord.

## What's next for Geodude?

Possibly adding more topics, and refining the loading of streetview images to better reflect the actual location.
## Inspiration

As college students learning to be socially responsible global citizens, we realized that it's important for all community members to feel a sense of ownership, responsibility, and equal access toward shared public spaces. Often, our interactions with public spaces inspire us to take action to help others in the community by initiating improvements and bringing up issues that need fixing. However, these issues don't always get addressed efficiently, in a way that empowers citizens to continue feeling that sense of ownership, or sometimes even at all! So, we devised a way to help FixIt for them!

## What it does

Our app provides a way for users to report Issues in their communities with the click of a button. They can also vote on existing Issues that they want Fixed! This crowdsourcing platform leverages the power of collective individuals to raise awareness and improve public spaces by demonstrating a collective effort for change to the individuals responsible for enacting it. For example, city officials who hear in passing that a broken faucet in a public park restroom needs fixing might not perceive a significant sense of urgency to initiate repairs, but they would get a different picture when 50+ individuals want them to FixIt now!

## How we built it

We started out by brainstorming use cases for our app and and discussing the populations we want to target with our app. Next, we discussed the main features of the app that we needed to ensure full functionality to serve these populations. We collectively decided to use Android Studio to build an Android app and use the Google Maps API to have an interactive map display.

## Challenges we ran into

Our team had little to no exposure to Android SDK before so we experienced a steep learning curve while developing a functional prototype in 36 hours. The Google Maps API took a lot of patience for us to get working and figuring out certain UI elements. We are very happy with our end result and all the skills we learned in 36 hours!

## Accomplishments that we're proud of

We are most proud of what we learned, how we grew as designers and programmers, and what we built with limited experience! As we were designing this app, we not only learned more about app design and technical expertise with the Google Maps API, but we also explored our roles as engineers that are also citizens. Empathizing with our user group showed us a clear way to lay out the key features of the app that we wanted to build and helped us create an efficient design and clear display.

## What we learned

As we mentioned above, this project helped us learn more about the design process, Android Studio, the Google Maps API, and also what it means to be a global citizen who wants to actively participate in the community! The technical skills we gained put us in an excellent position to continue growing!

## What's next for FixIt

An Issue’s Perspective

 \* Progress bar, fancier rating system

 \* Crowdfunding

A Finder’s Perspective

 \* Filter Issues, badges/incentive system

A Fixer’s Perspective

 \* Filter Issues off scores, Trending Issues
## Inspiration

As Engineering students, we tend to spend a lot of our time outside classes in the library working away on assignments. In the days following, we might even brag about how much time we spent working, and how much we were able to get done. However, up until now, there wasn't any concrete way to show this and compare to one another in this sudo competition.

## What it does

We created a web app that automatically tracks how long you spend studying in the library so that you can compete with friends and even make it to the top of the Study Spot leaderboard!

## How we built it

Your location is automatically detected using the Google Nearby Places API which biases its results to detect if a library is within a set radius from you. Then once your timer has started, it tracks your score and how long you've been studying for. Once you stop studying (by clicking the "stop studying" button or simply leaving the location), the score is then sent to the back-end database. These scores are compared and ultimately culminated into a leaderboard screen.

## Challenges we ran into

A lot of the team did not have previous experience with APIs. So naturally, we ran into a couple issue when working with the Verbwire API. We were, however, able to find a workaround to be able to ensure that our code is how we hoped!

## What we learned

Colin - Learning the basics of backend development and API calls
Jinwoo - Getting familiar with React.js
Jingyue - Front-end design (tailwind.css), React.js
Yax - How to use Firebase and Next.js authentication

## What's next for Study Spot

We have a couple of ideas for the development of study spot. The first one being to instead of using the NFT mints individually and displaying them, we hope to mint unique NFTs for each individual user. Another idea we hope to implement is a "search" feature, which can help the user navigate to the nearest library, which is particularly useful when working in a new location / area you might now know very well.