## 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

Growing tired of the same food at our college's dining hall, we decided to create "food hacks" by combining dishes from multiple vendors to enhance our experience, and share these on a Discord server. However, keeping track of a list of recipes inside chat is *cumbersome*, and our college additionally has a website to programatically pull menus from their food provider. Wanting to share our recipes to as many students as possible, we decided to create **Hack On Campus**: an all-in-one dining hall platform that allows you to share your own custom food creations.

## What it does

Our web app, Hack On Campus, pulls menus for colleges from *Dine On Campus* by Chartwells, a food provider for many colleges in the nation. We process the menus to allow people to create and share their own custom food combinations made with the dishes in their dining hall. Each recipe includes a list of dishes and vendors to visit, as well as a star-rating system so other students can rate how tasty the recipe is.

## How we built it

We utilized a Cloudflare stack for **complete serverless and edge deployment**. Our web app uses Cloudflare Pages for web hosting, Workers for serverless edge computing, KV for extremely fast and low-latency I/O, and D1 SQL for storing user data. Using this stack allows Hack On Campus to be deployed **globally** and run on the edge to users, resulting in **very quick response times**.

## Challenges we ran into

We originally planned to start the project using the new Deno 2.0 runtime. However, we quickly realized that we wouldn't be able to use the Cloudflare stack with it, so halfway through the project, we switched to using Node.js. We also had issues with Dine On Campus' API being very fragmented, having multiple different IDs for objects that we had to keep track of, coupled with the API being completely undocumented.

## Accomplishments that we're proud of

We're very proud of being able to run Hack On Campus using serverless technology and server-side rendering, allowing for a very snappy experience using our web app. We're also very happy that we can finally have a much easier way of sharing custom recipes, and that we can bring food hacking to more colleges, allowing any student to share the cool recipes they've made.

## What we learned

We learned the pressures of creating a full-stack app from frontend to backend. Especially for developing our frontend, we learned how crucial having our data in a consistent and organized manner is on our backend. Having issues with the backend makes it hard to implement the frontend when we have to backtrace to find issues with our internal APIs.

## What's next for Hack On Campus

We're planning to turn Hack On Campus into a production service that can be used at colleges that use Chartwells as their food provider. College students will be able to sign-in and share their own custom dishes with other students. We also want to expand Hack On Campus to pull menus from colleges that don't use Chartwells. Ideally, Hack On Campus becomes a positive feedback loop where anyone can share great food, and provide feedback to food providers on how to make the college dining hall experience better.
## Inspiration

Have you ever met someone, but forgot their name right afterwards?

Our inspiration for INFU comes from our own struggles to remember every detail of every conversation. We all deal with moments of embarrassment or disconnection when failing to remember someone’s name or details of past conversations.
We know these challenges are not unique to us, but actually common across various social and professional settings. INFU was born to bridge the gap between our human limitations and the potential for enhanced interpersonal connections—ensuring no details or interactions are lost to memory again.

## What it does

By attaching a camera and microphone to a user, we can record different conversations with people by transcribing the audio and categorizing using facial recognition. With this, we can upload these details onto a database and have it summarised by an AI and displayed on our website and custom wrist wearable.

## How we built it

There are three main parts to the project. The first part is the hardware which includes all the wearable components. The second part includes face recognition and speech-to-text processing that receives camera and microphone input from the user's iPhone. The third part is storing, modifying, and retrieving data of people's faces, names, and conversations from our database.

The hardware comprises an ESP-32, an OLED screen, and two wires that act as touch buttons. These touch buttons act as record and stop recording buttons which turn on and off the face recognition and microphone. Data is sent wirelessly via Bluetooth to the laptop which processes the face recognition and speech data. Once a person's name and your conversation with them are extracted from the current data or prior data from the database, the laptop sends that data to the wearable and displays it using the OLED screen.

The laptop acts as the control center. It runs a backend Python script that takes in data from the wearable via Bluetooth and iPhone via WiFi. The Python Face Recognition library then detects the speaker's face and takes a picture. Speech data is subsequently extracted from the microphone using the Google Cloud Speech to Text API which is then parsed through the OpenAI API, allowing us to obtain the person's name and the discussion the user had with that person. This data gets sent to the wearable and the cloud database along with a picture of the person's face labeled with their name. Therefore, if the user meets the person again, their name and last conversation summary can be extracted from the database and displayed on the wearable for the user to see.

## Accomplishments that we're proud of

* Creating an end product with a complex tech stack despite various setbacks
* Having a working demo
* Organizing and working efficiently as a team to complete this project over the weekend
* Combining and integrating hardware, software, and AI into a project

## What's next for Infu

* Further optimizing our hardware
* Develop our own ML model to enhance speech-to-text accuracy to account for different accents, speech mannerisms, languages
* Integrate more advanced NLP techniques to refine conversational transcripts
* Improve user experience by employing personalization and privacy features