基于图像识别的智能宠物猫狗喂养系统设计研究

Design and Research of An Intelligent Pet Cat and Dog Feeding System Based on Image Recognition

当今,饲养猫狗等宠物的人群逐渐增多。很多宠物主人因出差、旅游等难以随时照管宠物,导致宠物的健康得不到保证。如何在不影响正常生活和工作的基础上,方便、高效地照顾宠物,成为亟需解决的一个问题。基于此,文中以Raspberry Pi 3B+为核心装置,应用深度学习与图像识别等先进技术,探索设计了智能宠物猫狗喂养系统。该研究以红外感应系统与卷积神经网络模型为基础,并结合数字图像处理与图像识别分类技术,精准检测与判断宠物猫狗类别,依据检测结果进行精准喂食,从而使整个喂养过程更加智能化和简单化。这样不仅减少了宠物猫狗对主人的依赖性,且对改善人们的生活便利性与生态环境具有重要意义。

Nowadays,the number of people who keep pets such as cats and dogs is gradually increasing.Many pet owners find it difficult to take care of their pets at all times due to business trips,travel,and other reasons,resulting in the inability to ensure their physical health.How to take care of pets conveniently and efficiently without affecting normal life and work has become an urgent problem that needs to be solved.Based on this,this paper takes Raspberry Pi 3B+as the core device,applies advanced technologies such as deep learning and image recognition,and explores the design of an intelligent pet cat and dog feeding system.This study is based on infrared sensing systems and convolutional neural network models,combined with digital image processing and image recognition classification technology,to accurately detect and judge the categories of pet cats and dogs.Based on the detection results,precise feeding is carried out,making the entire feeding process more intelligent and simplified.This not only reduces the dependence of pet cats and dogs on their owners,but also has great significance for improving people̓s convenience in life and the ecological environment.