Mobile App Design Award News

Last week DreamWalk was announced as a finalist in the prestigious 2019 MUX Awards for our mobile app design work on the Recycle Mate app.


The innovative design revolves around a unique animated ‘object analysis’ theme. It’s unlike anything else on the market and fits perfectly with technical innovation that makes the product so memorable.

The MUX (mobile user experience) Awards is an internationally renouned mobile app design award honoring companies and designers leading the industry in mobile app design, animation and user experience.

Judges in the 2019 MUX Awards include Facebook head of design, Amanda,  Linden, Air BnB’s Alex Schliefer and Google’s head of UX Elizabeth Churchill. See more about the judges here.

Recycle Mate is among some amazing company with app designers from Evernote, RedBull TV, Starbuck and TED among the other finalists.

Recycle Mate is an artifical intelligence-powered app for iPhone and Android that helps users sort their recycling. Simply point your device camera at an object and Recycle Mate will tell you which bin it goes in, according to your local council guidelines.

The mobile app design was lead by DreamWalk’s Joseph Russell, with contributions from senior designer Ned Marquis.


2019 MUX Awards Finalists

The Recycle Mate app was designed and developed by Melbourne app developer, DreamWalk as a NSW state government initiative and launched by the NSW Environmental Protentions Agency (EPA) in conjunction with client Adaptation.

Mobile app design work was completed in 2019 by Joseph Russell and the app was developed and released by November of 2019.

The biggest design challenge was how to make something as inherantly boring as recycling engaging and fun. The solution Joseph came up with was to use bold and simple visuals in combination with animated object scan outcomes to make the app extremely user-friendly and satsfying to use.

Design tools used include Sketch, Adobe Photoshop, Adobe Illustrator, Adobe After Effects and Lotti.

The app uses its own custom-trained machine learning model to identify objects. The app is currently in public beta phase and only works in New South Wales. A full national rollout is planned for this year (2020) and more object training will commence in the next couple of months. This will dramatically improve the object detection performance and enable its use with councils around the world.


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