Utilizing Machine Learning for Developing a Pet Health Monitoring System

Abstract

Skin diseases in animals are a prevalent issue, making early diagnosis and treatment crucial for their health and well-being. This article introduces a machine learning-based animal health system designed to assess skin conditions. The system features a camera module that captures images of animal skin, which are then analyzed by machine learning models trained on a comprehensive database of health and disease images. Utilizing Convolutional Neural Networks (CNNs) for image classification, the system aims to identify various skin diseases, including dermatitis, eczema, and fungal infections. Upon detecting a skin disease, the system alerts pet owners to seek prompt treatment. Evaluation using skin disease image data demonstrated an accuracy rate of 92% in disease classification. These results suggest that the proposed system can enhance animal healthcare and management by detecting skin diseases early and effectively.