Smart Vending Machine

Smart Vending Machine is a project I worked on with 5 other teammates at DeeCamp - Artificial intelligence training camp hosted by Sinovation Ventures. For this project, we collaborated with AInnovation (https://www.ainnovation.com/en) in order to overcome the challenges that exist in their smart vending machine such as difficulty in distinguishing similar goods and quickly identify new products.
My Role
UX/UI Design, Visual Design, User Research, Usability Testing
Teammates
Xuesong Yao, Jianying Li, Yongqiang Li, Juanxian Cai, Yuan Yan
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Background

The Problem
The smart vending machine has become more and more popular due to its convenience and low maintenance cost. But some problems are still remained to be solved.
LOW ACCURACY RATE
 
The current model is more likely to make mistakes when distinguishing similar goods, the common method to overcome this problem is to avoid similar commodities appearing in the same vending machine.
NEW PRODUCTS
 
The packages are always updating and there are new products launching every day, it is impossible to retrain the model continuously to identify new products. It is very urgent to find a solution to these problems.
User Scenario
SCAN FACE
Users scan their faces to unlock the smart vending machine. Their face recognition result is connected to their personal account. 
TAKE ITEMS
Once the door opens, users can take any items they need from the smart vending machine.
CHECKOUT
Once the door closes, the smart vending machine will check out the items automatically and deduct money from users' personal account. 

Technical Solution

OBJECT DETECTION
The procedure consumes a lot of manpower and material resources, what’s worse,  it relies on a lot of data. So finding a way to pre-screen similar commodities by machine is a good way to save resources and improve work efficiency. By uploading the picture of the new products, the owners of the smart vending machine can find out the similarity between existing products and new products, if they are too similar, they should not be placed together, if they are quite different, they can be placed together.
FEW-SHOT CLASSIFICATION
Few-shot learning can be implemented based on distance metric representation with only 6 samples. The owner of the smart vending machine can upload 6 pictures of the new product in different angles, the new product can then be added to the commodity library and identified by the smart vending machine.

Design

BRAND IDENTITY
XiaoZhi - the smart vending machine. I designed the cute AI character in order to make the brand more accessible to younger audiences, who are more likely to use the smart vending machines.
LOGO DESIGN
I designed the logo for the smart vending machine app, which will be used by smart vending machine owners.
Wireframes
The app allows the smart vending machine owners to add new products and identify whether a product can be placed in the smart vending machine by themselves.

© 2020 by Queena Wang.