## Inspiration

Searching for your next coffee haunt can be time-consuming. Browsing Yelp or Google Maps involves a lot of filtering out Starbucks and McDonald's. Lists of the best coffee spots around town are scattered across various blogs and articles. And determining whether there are enough outlets or public WiFi available is simply a gamble you have to take.

We wanted to make it easy to find ALL the information about your next coffee shop - including the little things.

## What it does

Coffee Compass is a web application for coffee newcomers and enthusiasts alike, providing a large variety of recommendations for places to visit and can handle specialized questions so that you can find out anything about coffee and how you want to enjoy it.

## How we built it

We scraped a ton of information from review sites, blogs, and informational sites and compiled it all into a corpus for reference. We adapted an LLM to be able to answer questions related to coffee shops and their specialities with a sense of personality as well as dynamically recommend places according to user info.

The web application was designed with Figma, incorporating a chatbot conversational experience and passport incentive system to engage with users and keep them returning to Coffee Compass.

## Challenges we ran into

Verifying information across different sources was super important. LLMs are more likely to hallucinate if they don't have accurate, verified information. It's a huge bummer to go to a great coffee shop by the beach, only to realize it doesn't have WiFi for your nifty MacBook Air. For the remote working crowd, even little things like outlets can matter. Being able to answer these questions gives a lot of value.

## Accomplishments that we're proud of

Prioritizing design and making sure the user experience is something that a user would really enjoy using. We really liked gamifying some aspects to reward coffee aficionados for their passion.

## What we learned

Figuring out user workflow can be challenging, and there are lots of ways to tackle problems. Different kinds of users have their own problems, and that can potentially lead to design conflicts.

## What's next for Coffee Compass

Build out the gamified passport experience so that visitors who visit coffee shops feel rewarded for their passion. Continuing to build out an extensive database of features for coffee shops that people care about and getting enhanced visuals for every coffee shop, so that users can really feel like they can explore the coffee shop before heading out there for a cup of joe.
## Inspiration

Our inspiration behind creating this app stems from our own experiences as university students. We understand the hectic schedules, academic pressures, and limited time that come with the territory. As students ourselves, we often found it challenging to make healthy and mindful food choices while juggling our studies and other commitments. This inspired us to develop a solution that not only simplifies the process of finding suitable meals in the campus dining hall but also caters to individual dietary restrictions and preferences. We want to empower fellow students to effortlessly make informed food choices that align with their goals, whether it's staying within a certain calorie range, accommodating dietary restrictions, or simply enjoying a satisfying meal. Our aim is to provide a convenient, time-saving, and health-conscious solution for university students, making their dining hall experience more enjoyable and stress-free.

## What it does

Our app is designed to streamline the dining experience for university students by providing a tailored and efficient solution. It serves as a comprehensive food companion, allowing users to search through their university dining hall menus with precision. What sets our app apart is its ability to cater to individual dietary needs and preferences. Users can input specific criteria, such as a calorie limit, and our app will generate a selection of three dishes that meet these requirements. This not only saves valuable time but also helps students make healthier and more mindful food choices. Additionally, the app provides nutritional information, allergen alerts, and even offers recommendations based on past selections, ensuring that every meal is not only delicious but also aligns with the user's unique dietary considerations. Ultimately, our app simplifies the process of finding the perfect meal, making dining on campus a more enjoyable and stress-free experience.

## How we built it

We use html and css for the frontend. We used flask and python for backend. We use webscraping to filter out key information for the menu websites.

## Challenges we ran into

We ran into a lot of challenges. First, we had a completely different idea yesterday and we spent 5 hours trying to implement that idea into a prototype. However, after talking to the mentors, we decided to do a completely different project.

Another challenge that we went through was the connecting the front end and the backend. We had trouble with the post request. The algorithm in the backend was also troubling at some point. Our ideas were all over the place. Communication was also not at its best

## Accomplishments that we're proud of

We had a big brainstorm moment where we just pitch ideas. This improved teamwork and collaboration

## What we learned

There were so much things to learn about coding and and creating projects. Creating projects in a team involves constant communication and collaboration. Explanation of thoughts is very important for teamwork

## What's next for Uni.Eats

We are trying to make the project more advanced where there are more input information and thus more permutations for the amount of input we have. Thus, we can have information besides calories such as a filter for a vegan options, dietary restrictions, and more food facts
## Inspiration

Travel planning is a pain. Even after you find the places you want to visit, you still need to find out when they're open, how far away they are from one another, and work within your budget. With Wander, automatically create an itinerary based on your preferences – just pick where you want to go, and we'll handle the rest for you.

## What it does

Wander shows you the top destinations, events, and eats wherever your travels take you, with your preferences, budget, and transportation in mind. For each day of your trip, Wander creates a schedule for you with a selection of places to visit, lunch, and dinner. It plans around your meals, open hours, event times, and destination proximity to make each day run as smoothly as possible.

## How we built it

We built the backend on Node.js and Express which uses the Foursquare API to find relevant food and travel destinations and schedules the itinerary based on the event type, calculated distances, and open hours. The native iOS client is built in Swift.

## Challenges we ran into

We had a hard time finding all the event data that we wanted in one place. In addition, we found it challenging to sync the information between the backend and the client.

## Accomplishments that we're proud of

We’re really proud of our mascot, Little Bloop, and the overall design of our app – we worked hard to make the user experience as smooth as possible. We’re also proud of the way our team worked together (even in the early hours of the morning!), and we really believe that Wander can change the way we travel.

## What we learned

It was surprising to discover that there were so many ways to build off of our original idea for Wander and make it more useful for travelers. After laying the technical foundation for Wander, we kept brainstorming new ways that we could make the itinerary scheduler even more useful, and thinking of more that we could account for – for instance, how open hours of venues could affect the itinerary. We also learned a lot about the importance of design and finding the best user flow in the context of traveling and being mobile.

## What's next for Wander

We would love to continue working on Wander, iterating on the user flow to craft the friendliest end experience while optimizing the algorithms for creating itineraries and generating better destination suggestions.