DeepRemote: A Smart Remote Controller for Intuitive Control through Home Appl...Yuta Takahashi
This document describes DeepRemote, a smart remote controller that uses deep learning for intuitive home appliance selection and control. It consists of a control unit with a camera and buttons and a deep learning unit for appliance recognition. The system was tested for classification accuracy of over 80% on average, response time of under 2 seconds, and faster control times than traditional remotes in user tests. Overall, DeepRemote demonstrates an effective deep learning approach for selecting and controlling home appliances intuitively with a single remote controller.
An Identification Method of IR Signals to Collect Control Logs of Home Applia...Yuta Takahashi
This document proposes a method to identify infrared (IR) signals from home appliances in order to collect control logs. It involves preprocessing raw IR signals into pulse width sequences, comparing signals using mean absolute error and sum absolute error, and constructing statistical models to identify appliance type with 95.5% accuracy and command type with 92% accuracy based on a database of 1,400 signals from 14 appliances. A simple simulation shows identification stability is achieved when the database includes 6 or more signals per appliance. The method could help automatically understand user preferences from appliance usage logs.