## Inspiration

Public washrooms can be a rough time for users thanks to lots of traffic, clogged toilets, missing toilet paper and more. There’s rarely opportunities to easily provide feedback on these conditions. For management, washrooms often get cleaned too frequently or rarely at all. Let’s bring simple sensors to track the status of frequently used facilities to optimize cleaning for businesses and help users enjoy their shit.

## What it does

System of IoT sensors, opportunity for gesture-based user feedback, streamed to a live dashboard to give management updates
We track:
-Traffic into washroom
-Methane levels
-Fullness of trash cans
We provide:
Refill buttons in each stall
Prompt for facility rating using Leap Motion gesture tracking

## How we built it

Used Snapdragon to attach three sensors for data collection purpose to track cleanliness in washroom
Used Leap Motion to create interactive dashboard to rate they experience through gestures - more sanitary and futuristic approach, incentivizing users to participate
All data pushed up to Freeboard where management can see the status of their washrooms

## Challenges we ran into

Tricky using documentation with Leap Motion, didn’t take into account web apps need time to load, wouldn’t load body; also challenging to build hand recognition from the ground up
Getting hardware to work: Snapdragon with shield doesn’t have documentation - normal arduino code wasn’t working
Integrating data with IoT dashboard

## Accomplishments that we're proud of

Found cool solution to get data from sensors to dashboard: wrote to serial, read that,
used a python script, and then used dweet.io to publish to freeboard
Building hand recognition in Leap Motion

## What we learned

Learned to use Leap Motion
Live data transmission with multiple sensors
Integrating a ton of IoT data

## What's next for Facile

Store data online so that we can use ML to understand trends in facility behaviour, cluster types of facilities to better estimate cleaning times
Talk to facilities management staff - figure out current way they rate and clean their washrooms, base sensors on that
Partnering with large malls, municipal governments, and office complexes to see if they’d be interested
Applicable to other environments in smart cities beyond bathrooms
## Inspiration

[www.loolooloo.co](http://www.loolooloo.co) is inspired by the famous Waterloo chant—Water Water Water! Loo Loo Loo! And, of course, the natural consequence of drinking lots of water, water, water, being a visit to the loo, loo, loo!

## What it does

[www.loolooloo.co](http://www.loolooloo.co) detects when you go to a water fountain, and sends you a text message with a custom link to an interactive map that gives you directions to the nearest bathroom. It also has a daily water tracker that incentivizes you to stay hydrated.

## How we built it

We utilized the MappedIn API to implement an indoor navigation system for building maps. The front-end was developed using React, while the back-end was powered by Node.js. Twilio's API was integrated to enable SMS notifications with custom map links.

## Challenges we ran into

Deploying a Bluetooth beacon to detect user proximity and send real-time requests to an HTTPS port proved to be a complex task, particularly in managing secure communications and ensuring reliable detection within a defined radius.

## Accomplishments that we're proud of

We successfully built a fully functional system where the front and back ends work seamlessly together, delivering a real-time user experience by sending SMS directions to the nearest restroom whenever a user approaches a water fountain.

## What we learned

We gained valuable experience in integrating proximity detection systems with cloud services, handling real-time data, and optimizing our full stack application for responsive and secure user interactions.

## What's next for [www.loolooloo.co](http://www.loolooloo.co)

Future plans include enhancing the system's accuracy, and making the UI more user friendly.
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