## Inspiration

It's a warm, sunny day; you walk out to get food at your favorite place, only to find no place available to enjoy the wholesome dining experience. This has only gotten common after COVID-19 thanks to capacity limits, and even when the limits will be gone, people crave the convenience they once had of reserving, reserving, and reserving. And hence comes the need for Queueless!

## What it does

Free for customers, and subscription-based for businesses who choose to participate, Queueless gives live status of the number of tables and seats available in the restaurants of your choosing. As a result, small restaurant owners would get a constant supply of happy customers who prefer last-minute plans.

## How we built it

Used Python for early development and proof-of-concept, such as on the Restaurant Owner side of "operations". Google Cloud/Firebase is used for the database. And HTML and Google Maps API for deployment and User Search end.

## What's next for Queueless (for Restaurants)

Predicting when the tables will be vacant if all are occupied based on each restaurant's history and . Expanding this to other business like barber shops, bars etc.
## Inspiration

With half of our team working in the food industry, we saw firsthand the staggering amount of food wasted daily. This inspired us to act, creating a solution that not only reduces food waste but also helps those who are uncertain about where their next meal will come from. FoodBridge was born from our drive to make an immediate impact on both restaurants and the community.

## What it does

FoodBridge is more than just an app—it's a non-profit 501(c)(3) initiative that gives local restaurants the opportunity to donate their untouched, excess food in exchange for valuable business services. From waste management and deep cleaning to streak-free glass maintenance and free publicity, FoodBridge supports sustainability while offering practical benefits to restaurant owners.

## How we built it

* **Front end:** HTML/CSS
* **Backend:** Next.js server, facilitating the external server's functionality
* **Database and Storage:** Google Firebase: Chosen for its scalability and real-time database capabilities, Firebase efficiently stores and retrieves data related to user profiles and shared inventory.
* **User Authentication:** Users, both restaurants and those in need, can securely log in and log out, ensuring a personalized experience and custom pages depending on the role.
* **Inventory:** Restaurants have a personal inventory where they can add food they would like to donate. They also have to include an image of the item and the date of expiration.
* **Recipients Inventory:** Recipients can see all the available food from all restaurants. They would be able to see the name and address of the restaurant, the image uploaded, and the expiration date. They would also have the ability to reserve that item.
* **Cross Inventory Management:** Whenever recipients pick up food, the food gets popped from the restaurant's database and goes to a different section reserved.
* **Spotlight:** A page where we weekly give a shoutout to the restaurants that donated the most amount of food in a week.

We started with big ambitions, planning to use Next.js and Google Firebase. However, with the intense 36-hour hackathon timeline, we made the strategic decision to focus on the essentials. We pivoted and built the project using HTML and CSS, prioritizing a sleek, functional front-end to ensure our vision was not just a concept but something we could present while we keep building the structure of the app.

## Challenges we ran into

During the hackathon, we faced several challenges that required adaptability and quick decision-making. Designing a NoSQL database schema to efficiently manage user data and interactions was a significant hurdle due to the steep learning curve. Additionally, we developed two distinct home pages for logged-in users—one for restaurants and one for recipients—further adding to the complexity. However, time constraints proved to be our greatest challenge. Although we initially planned to utilize more advanced technologies, we quickly realized the importance of adjusting our approach. We streamlined our tech stack, focusing on the essential elements of our project, which allowed us to maintain the integrity of our core idea while meeting the tight deadline and delivering a functional, high-quality product.

## Accomplishments that we're proud of

Despite the intense timeline and scaling back, we successfully created a fully working app that brings our vision of sustainability and business support to life. Our focus on creating something tangible and impactful within 36 hours is a huge win for our team.

## What we learned

Throughout the project, we gained valuable experience in both technical development and team collaboration. Tackling a NoSQL database schema for scalable data management was a steep learning curve, but it taught us the importance of structuring data efficiently for diverse user interactions. We also honed our skills in React.js and Firebase, learning how to handle authentication, real-time data storage, and dynamic routing for different user experiences.
Beyond the technical challenges, we learned how to adapt quickly in a fast-paced environment. Time constraints required us to prioritize features and focus on delivering a functional product, which taught us how to make strategic trade-offs without compromising the quality of our core idea. Working as a team under these conditions also improved our collaboration and communication skills, ensuring all components of the project came together seamlessly. Finally, we deepened our understanding of user-centric design, tailoring distinct experiences for both restaurants and recipients to create a practical and intuitive interface.

## What's next for FoodBridge

Scalability options:

1. Expand to not only food from restaurants but also start including supermarkets, making the app more accessible to everyone.
2. Change the tech stack by implementing a SQL database instead of a NoSQL database.
3. Smoother UI/UX.
4. iOS and Android support.
5. Sort restaurants by how close they are to the recipient.

We came into this hackathon with a mission, and through creativity, teamwork, and relentless execution, we’re confident we’ve built something truly game-changing with FoodBridge.
## Inspiration

The COVID-19 pandemic has changed the way we go about everyday errands and trips. Along with needing to plan around wait times, distance, and reviews for a location we may want to visit, we now also need to consider how many other people will be there and whether its even a safe establishment to visit. *Planwise helps us plan our trips better.*

## What it does

Planwise searches for the places around you that you want to visit and calculates a PlanScore that weighs the Google **reviews**, current **attendance** vs usual attendance, **visits**, and **wait times** so that locations that are rated highly, have few people currently visit them compared to their usual weekly attendance, and have low waiting times are rated highly. A location's PlanScore **changes by the hour** to give users the most up-to-date information about whether they should visit an establishment. Furthermore, PlanWise also **flags** common types of places that are prone to promoting the spread of COVID-19, but still allows users to search for them in case they need to visit them for **essential work**.

## How we built it

We built Planwise as a web app with Python, Flask, and HTML/CSS. We used the Google Places and Populartimes APIs to get and rank places.

## Challenges we ran into

The hardest challenges weren't technical - they had more to do with our *algorithm* and considering the factors of the pandemic. Should we penalize an essential grocery store for being busy? Should we even display results for gyms in counties which have enforced shutdowns on them? Calculating the PlanScore was tough because a lot of places didn't have some of the information needed. We also spent some time considering which factors to weigh more heavily in the score.

## Accomplishments that we are proud of

We're proud of being able to make an application that has actual use in our daily lives. Planwise makes our lives not just easier but **safer**.

## What we learned

We learned a lot about location data and what features are relevant when ranking search results.

## What's next for Planwise

We plan to further develop the web application and start a mobile version soon! We would like to further **localize** advisory flags on search results depending on the county. For example, if a county has strict lockdown, then Planwise should flag more types of places than the average county.