Product Design of Ecobin App for Hackathon

The product Design of a Garbage sorting App using machine learning & location to sort it into correct bin.

UX & UI

Front-end

Team

Educate & Make an
Impact in Recycling

Problem Statement

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

Target Audience

Target Audience is 14 to 35 with the characteristics of a busy life style, consistently have their phone on them, prefer to be eco-friendly but does not always go out of their way. They are often confused on the best way to recycle. Their main pain points is spending too much time to sort, not having an accessible tool to use, awareness, and the motivation to build a eco-friendly habit.

Team Dynamic & Role

My Role & Team

Our team consistent of four individuals who took roles of Business Analyst, Developer, Data Scientist and myself - UX & UI and front-end. I took part in ideating the problem statement, the solution and the presentation as well. Our team was chosen for us; therefor, when I arrived at the hackathon I had not met the other members before the day of the hack.

Challenges

Ideate, Design &
Develop in 24 Hours

icon

24 Hours to Design
develop & present

icon

We were
all Strangers

icon

Project
management

icon

Burn Out

icon

5 Minutes
to Present

icon

Aim to be 1st:
$5000 Award

Frustration Leading to Discovery

Discovery of the problem was expressing our frustrations of daily interactions. Recycling was a prime example of a struggle I faced. It was a realization that others faced the same challenge.

Sorting the experience

Process

Defining the problem statement and understanding the pain points came next. A product criteria was developed: it must beaccessible, fast, educative, adoptable for businesses, lower cost and motivative . We developed solutions: camera sorting, trash geolocation, strong user experience for fast navigation, gamification for motivation, and data collection. One dedicated Userflow was decided upon. Once the wireframe was developed, I spoke to others to receive feedback. Afterwards, a style guide was developed and the prototype was made. I coded four pages of the front-end as a web application, working along side the developer to meet requirements.

Product Criteria

icon

Accessible

icon

Time Spent

icon

Educating

icon

Adoptability For Businesses

icon

Cost for Applying Product

icon

Motivation

Solution

Web Application that uses machine learning to sort items into the correct bin using: user's location, QR code to activate & gamification to motivate

icon

Accessible

icon

Time Spent

icon

Educative

icon

Adoptability For Businesses

icon

Cost for Applying Product

icon

Motivation

How the solution performed out of 5 (5 being the highest) in comparison to our other ideas

Ecobin UI & Features

ecobin ecobin ecobin

Frustration Leading to Discovery

Ultimately, we reached our goal. We developed the Userflow that we determined was right for the presentation. We ran into trouble where the code broke near the last few hours but we managed to allocate time to fix the issue. I paired with the business analyst to finish the presentation, while the developer and data scientist worked to fix the problem.

Team Ecobin won first place from a successful presentation, solution, design and proof of concept.