EcoBin: RBC Hackathon 1st Place

Garbage sorting App using machine learning & location to sort it into the right bin.

  • UX/UI
  • HTML/CSS
  • Teamwork
  • Problem Solving

How can we educate Canadians on the benefits of recycling properly and reduce the economic impact of contaminated recyclables?

Tools

  • ADOBE XD
  • HTML/CSS

Skills

  • Problem Solving
  • Ideating
  • Teamwork
  • Time management
  • Presenting

Roles

  • UX/UI
  • Front-end

Teammates

  • UX/UI: Risi Zani
  • Business Analyst: Danial Sheikh
  • Developer: Hasaan Sommro
  • Data Scientist: Wei Liu

Project Challanges

24 Hour Hack

4 individuals with different fields of study whom never met collaborating

  • • Allocating time for different phases of the project within 24 Hours.
  • • Understanding & learning the valuable knowlege and perspectives of Teammates
  • • Communicating design and the importance of certain elements
  • • Developing solutions to project breaking issues within code or new found secondary research
  • • Allocating some team bonding time, sleeping when there's work to be done, not over snacking

The Problem

In some communities Educating Youth on Recycling has been reduced or cancelled because of taxes.

I demonstrated my frustration of sorting garbage and how I've seen others feel the same.

Do you feel the same?

Pain Points

  • • Accessibility of a tool to sort garbage with ease
  • • Frustration of spending extra time standing by the garbage bins to decode the material
  • • Finding the drive/motivation to build up an eco-friendly habit

Factors to consider

  • • Adopitablity for other businesses or locations to impliment
  • • A method to educate users at the same time
  • • Usable for a wide audience

Project Goal

A product that is easily accessible to users that not only sorts garbage into the correct bin but also educates and motivates them to maintain this habit. In addition, to being adoptable in many different settings and for other businesses.

Target Audience

For the purpose of the hackathon, we are targeting young adults to adults whom are already consistently have their phones on them.

Measure of Success

Proof of concept. Machine learning should be able to detect the difference between cardboard and garbage. The main and camera page at a minumium must be coded. Presenting for 3 and thirty seconds and leaving the rest for questions for presentation.

Platform

The platform we decided on would be mobile. A mobile app that sorts garbage with a click of a button.

It's quick, adoptable & accessible because society has integrated phones in their daily life.

The second concept, was having a device in the garbage bin itself to sort out the gabrage. However, an mobile app, relays less on companies or locations to implement in each garbage bin (which I assume would be more difficult to push for this change and costly).

Features

Design

Minimalistic design that uses color mainly as an affordance for navigation

Colour Scheme

Trendy, Earthy, Minimalistic

  • • Vibrant green & blues to replicate earth's colors.
  • • Positive, calming & encouraging colors
  • • Dominantly using a white due to contrast, simplicity and familiarity
    • Typography

      • • Museo-Sans. Geometric sans-serif font
      • • Easy to read even at smaller fonts
      • • Size 14 to 16 font for better readability

Reflection

Team Ecobin Won!

  • • Working with different perspectives is a gift
  • • Machine Learning reached 65% accuracy, All Pages but profile was coded
  • • How to handle project obstacles in a short amount of time
  • • Learning to use real experiences to solve problems
  • • Bonding with your team is vital to group working dynamic
  • • Problem solving is what interests me the most
  • • How the User interface and userflow can be shifted for a better experience
  • • Asking other designers from different groups despite being in a competition on their critique was helpful
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How in twenty four hours?

  • • Seperating into two seperate groups, while providing feedback and communicating to each other
  • • Locating time for choosing our topic, ideation, problem solving, research, pain points, designing, coding and presentation
  • • While I worked on sitemaps, design and doing some research with the business analyst, back-end & data scientist worked on getting machine learning functioning and integerating it into web.
  • • Switching to communicate to back-end on how front-end/interface code worked. Then helping business analyst on presentation
  • • Being honest and communciate with eachother to create a level of understanding through different fields. Providing critique

Learn more about me here!
Contact me at: zani@sheridancollege.ca

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