What it does

Nowadays, people have become more health-conscious; they want to know what they are eating and how it will taste. EatÆR will help our customers to achieve this task, as well as reducing food and financial wastage. Our application has the capability to visualize the menu restaurant trends along with features to automatically update the restaurant menu database. Moreover, with our app, consumers now have the ability to set their own pick-up time for a particular dish from the restaurant.

How we built it

We built the application framework at adalo.com and imported 3D assets onto EchoAR.

Challenges we ran into

Connecting the live restaurant menu database with the EchoAR platform.

Accomplishments that we're proud of

Creating this startup application that can both improve customer experience and the restaurant transparency.

What we learned

  • Time management skills
  • Handling of different relations among the databases
  • Explored EchoAR capabilities
  • App Building
  • Designing

How EatÆR can help Restaurants

  1. Improving visibility: Augmented reality restaurant menus can be customized to show information about each dish, such as 360-degree visualizations, details of ingredients used, portion sizes, calorie, and nutrition info, etc.
  2. Upsell: AR food menus can also help restaurants sell more items. Apps can be programmed to suggest ideal complements to selected dishes such as appetizers, beverages, dessert combos, etc.
  3. Improve customer engagement: Unlike traditional food menus, AR food apps can be customized to display a wealth of content on demand.

What's next for EatÆR

The limitation of the current version is that the restaurant owners may have to recruit a 3D artist or be proficient in Unity to have a 3D model of their dish, so we are considering creating an API between the application with a photogrammetry software. This would allow the restaurant owners to instantly create 3D models of their dish by just photographing it in different angles. To ensure that the 3D model quality is equal for every restaurant, we are also thinking about implementing a neural network model to drastically generalize photo quality.

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