The Design of Smart Suitcase

With the development of the Internet of Things (IOT) and the wave of artificial intelligence (AI), more and more embedded systems combine AI to make life easier and more convenient for people. This paper integrates image recognition and object-following techniques to create an intelligent AI suitcase. By recognizing the back view of the user, the smart suitcase can move and follow the user with appropriate speed. When the user is too close, the suitcase performs corresponding actions to slow down or to stop to avoid collision; while the user is too far away, the suitcase will accelerate to maintain the distance between the users to avoid of losing connection with user. For image processing, we use Convolutional Neural Networks (CNN) as our algorithm and OpenCV for implementation to achieve object recognition and tracking. The Wi-Fi module is installed on the suitcase, it serves to detect whether the target is missing by connecting to the user's mobile phone. When the detected Wi-Fi signal is too low, the mobile phone will issue a warning to remind the user that the luggage distance is too far. In terms of control, we use fuzzy control and machine learning to control the motor to make tracking of the user more stable.