• Aakash A V
• Abhinav A S
• Abhiram Madhu Mundani
• Ananthu S S
• Nagaraja Hebbar N

The identification and diagnosis of diseases in dogs have historically depended on the skills of veterinarians, frequently involving labor-intensive manual methods. This study presents an AI-driven system designed for the automatic identification of canine illnesses through deep learning approaches, particularly utilizing Convolutional Neural Networks (CNNs). The system analyzes images of dogs to diagnose various diseases, trained on a comprehensive dataset of labeled canine images. The study addresses challenges such as image quality variability, the need for high-quality annotated datasets, and model optimization for mobile and real-time deployment. This system investigates the integration of IoT tools to improve monitoring and diagnostic processes in veterinary care. The findings highlight how AI can enhance disease identification by enabling faster and more accurate diagnostics in canine health management.

Artificial Intelligence, Canine Disease Recognition, Convolutional Neural Networks, Veterinary Diagnostics, Image Classification.

"CANAI: AI-ASSISTED CANINE DISEASE RECOGNITION SYSTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.874-879, July-2025, Available :http://www.jetir.org/papers/JETIRGX06166.pdf

"CANAI: AI-ASSISTED CANINE DISEASE RECOGNITION SYSTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp874-879, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06166.pdf