• The Journal of the Korea Contents Association
• /
• v.19 no.5
• /
• pp.259-267
• /
• 2019

As the change in social awareness regarding cats is consistent with the lifestyle of modern people who seek an independent life, the number of cats owned as a pet and its market will continue to increase. The compainion animals are not just pets to pet owners, but people communicate with their pets and the pets have begun to be recognized as a member of their family. Although the pet industry has been steadily growing and the number of cats owned by households is rapidly increasing, there is a lack of study on products based on understanding the characteristics and behavior of cats. The purpose of this study is to propose a versatile furniture design considering the behavior characteristics of cats. The versatile furniture that is easy to move and rearrange according to necessity and the environment of residential space always pays to make better use of the space. We would like to propose versatile furniture that can satisfy the aesthetic pleasures of cats and can be used as furniture at the same time depending on purpose and situation. This study aims to develop the design of furniture that can make a better environment for pets and pet owners, an it is expected to be a basic study of furniture design for them.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.1
• /
• pp.22-27
• /
• 2020

Recently, as the number of households raising pets increases due to the increase of single households, there is a need for a system for monitoring the status or behavior of pets. There are regional limitations in the monitoring of pets using domestic CCTVs, which requires a large number of CCTVs or restricts the behavior of pets. In this paper, we propose a mobile system for detecting and tracking cats using deep learning to solve the regional limitations of pet monitoring. We use YOLO (You Look Only Once), an object detection neural network model, to learn the characteristics of pets and apply them to Raspberry Pi to track objects detected in an image. We have designed a mobile monitoring system that connects Raspberry Pi and a laptop via wireless LAN and can check the movement and condition of cats in real time.