## Inspiration

Have you ever had to stand in line and tediously fill out your information for contact tracing at your favorite local restaurant? Have you ever asked yourself what's the point of traffic jams at restaurants which rather than reducing the risk of contributing to the spreading of the outbreak ends up increasing social contact and germ propagation? If yes, JamFree is for you!

## What it does

JamFree is a web application that supports small businesses and restaurants during the pandemic by completely automating contact tracing in order to minimize physical exposure and eliminate the possibility of human error in the event where tracing back on customer visits is necessary. This application helps support local restaurants and small businesses by alleviating the pressure and negative impact this pandemic has had on their business.

In order to accomplish this goal, here's how it would be used:

1. Customer creates an account by filling out the required information restaurants would use for contact tracing such as name, email, and phone number.
2. A QR code is generated by our application
3. Restaurants also create a JamFree account with the possibility of integrating with their favorite POS software
4. Upon arrival at their favorite restaurant, the restaurant staff would scan the customer's QR code from our application
5. Customer visit has now been recorded on the restaurant's POS as well as JamFree's records

## How we built it

We divided the project into two main components; the front-end with react components to make things interactive while the back-end used Express to create a REST API that interacts with a cockroach database. The whole project was deployed using amazon-web services (serverless servers for a quick and efficient deployment).

## Challenges we ran into

We had to figure out how to complete the integration of QR codes for the first time, how to integrate our application with third-party software such as Square or Shopify (OAuth), and how to level out the playing field with the adaptability of new technologies and different languages used across the team.

## Accomplishments that we're proud of

We successfully and simply integrated or app with POS software (e.g. using a free Square Account and Square APIs in order to access the customer base of restaurants while keeping everything centralized and easily accessible).

## What we learned

We became familiar with OAuth 2.0 Protocols, React, and Node. Half of our team was compromised of first-time hackers who had to quickly become familiar with the technologies we used. We learnt that coding can be a pain in the behind but it is well worth it in the end! Teamwork makes the dream work ;)

## What's next for JamFree

We are planning to improve and expand on our services in order to provide them to local restaurants. We will start by integrating it into one of our teammate's family-owned restaurant as well as pitch it to our local parishes to make things safer and easier. We are looking into integrating geofencing in the future in order to provide targeted advertisements and better support our clients in this difficult time for small businesses.
**Inspiration**
Toronto ranks among the top five cities in the world with the worst traffic congestion. As both students and professionals, we faced the daily challenge of navigating this chaos and saving time on our commutes. This led us to question the accuracy of traditional navigation tools like Google Maps. We wondered if there were better, faster routes that could be discovered through innovative technology.

**What it does**
ruteX is an AI-driven navigation app that revolutionizes how users find their way. By integrating Large Language Models (LLMs) and action agents, ruteX facilitates seamless voice-to-voice communication with users. This allows the app to create customized routes based on various factors, including multi-modal transportation options (both private and public), environmental considerations such as carbon emissions, health metrics like calories burned, and cost factors like the cheapest parking garages and gas savings.

**How we built it**
We developed ruteX by leveraging cutting-edge AI technologies. The core of our system is powered by LLMs that interact with action agents, ensuring that users receive personalized route recommendations. We focused on creating a user-friendly interface that simplifies the navigation process while providing comprehensive data on various routing options.

**Challenges we ran into**
Throughout the development process, we encountered challenges such as integrating real-time data for traffic and environmental factors, ensuring accuracy in route recommendations, and maintaining a smooth user experience in the face of complex interactions. Balancing these elements while keeping the app intuitive required significant iterative testing and refinement.

**Accomplishments that we're proud of**
We take pride in our app's simplistic user interface that enhances usability without sacrificing functionality. Our innovative LLM action agents (using fetch ai) effectively communicate with users, making navigation a more interactive experience. Additionally, utilizing Gemini as the "brain" of our ecosystem has allowed us to optimize our AI capabilities, setting ruteX apart from existing navigation solutions.

**What we learned**
This journey has taught us the importance of user feedback in refining our app's features. We've learned how critical it is to prioritize user needs and preferences while also staying flexible in our approach to integrating AI technologies. Our experience also highlighted the potential of AI in transforming traditional industries like navigation.

**What's next for ruteX**
Looking ahead, we plan to scale ruteX to its full potential, aiming to completely revolutionize traditional navigation methods. We are exploring integration with wearables like smartwatches and smart lenses, allowing users to interact with their travel assistant effortlessly. Our vision is for users to simply voice their needs and enjoy their journey without the complexities of conventional navigation.
## Inspiration

Ideas for interactions from:

* <http://paperprograms.org/>
* <http://dynamicland.org/>
but I wanted to go from the existing computer down, rather from the bottom up, and make something that was a twist on the existing desktop: Web browser, Terminal, chat apps, keyboard, windows.

## What it does

Maps your Mac desktop windows onto pieces of paper + tracks a keyboard and lets you focus on whichever one is closest to the keyboard. Goal is to make something you might use day-to-day as a full computer.

## How I built it

A webcam and pico projector mounted above desk + OpenCV doing basic computer vision to find all the pieces of paper and the keyboard.

## Challenges I ran into

* Reliable tracking under different light conditions.
* Feedback effects from projected light.
* Tracking the keyboard reliably.
* Hooking into macOS to control window focus

## Accomplishments that I'm proud of

Learning some CV stuff, simplifying the pipelines I saw online by a lot and getting better performance (binary thresholds are great), getting a surprisingly usable system.

Cool emergent things like combining pieces of paper + the side ideas I mention below.

## What I learned

Some interesting side ideas here:

* Playing with the calibrated camera is fun on its own; you can render it in place and get a cool ghost effect
* Would be fun to use a deep learning thing to identify and compute with arbitrary objects

## What's next for Computertop Desk

* Pointing tool (laser pointer?)
* More robust CV pipeline? Machine learning?
* Optimizations: run stuff on GPU, cut latency down, improve throughput
* More 'multiplayer' stuff: arbitrary rotations of pages, multiple keyboards at once