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Plug+

Plug+

A simple audio-trainable switch for your home

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While products have been designed and manufactured to serve a predefined use, logic, and behaviour, with advances in emerging technologies such as machine learning, increasingly objects are acquiring the capability of learning, context-awareness, and evolving affordances. This paradigm shift brings new models of interactions between people and objects. New complexities inside objects also bring challenges for designers to translate and bridge the gap in understanding these interaction.

How can we create new metaphors of interaction with intelligent objects?
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What language should we use to communicate objects’ learning process? What new values can this kind of trainable intelligence bring to us?

  • Expose the method of training and provide an interface for it?

  • Move from smart assistive devices to devices that feel like uniquely yours?

 
Plug+ is a trainable switch that explores a model of voice interaction in the future intelligent home using machine learning.
 
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Concerns around privacy of cloud-based IoT devices is at a high

Concerns around privacy of cloud-based IoT devices is at a high

 

Prototyping

The prototype consists of two part, a switch box that allows you to connect any of your appliances, and a detachable training module that you can place anywhere in your home and train it with your unique voice command.

Plug+ is built on Arduino and Wekinator, which enables it to be trained and used locally, making it a more reliable, free from concerns about data and privacy in cloud-based systems. We designed a simple training interface, using LED and the change of the light, different modes such as training and using modes can be indicated. More importantly, it provides a direct and understandable feedback to demonstrate the training progress. The modular design enables you to connect Plug+with any appliances and use it in different scenarios.

 

Team: Yuxi Liu, Varenya Raj
Role: Programming in Arduino and training in Wekinator
Guides: Massimo Banzi and Simone Rebaudengo