Ai-driven pet care app for virtual assistance and symptom diagnosis

Nivika Prasad, Kashi Nath (2025) Ai-driven pet care app for virtual assistance and symptom diagnosis. Final Year Project, UTAR.

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Abstract

Pet ownership brings joy but also significant responsibilities in health management and care. Existing applications often offer fragmented features, lack reliable information, and fail to assist owners in assessing urgent medical concerns. To address these challenges, this project presents PawHub, a mobile application that integrates artificial intelligence with comprehensive pet care tools to deliver a unified, user-friendly experience. The system was developed using the Agile methodology, leveraging React Native for cross-platform frontend development, Node.js with Express for the backend, and Supabase as the centralized database and authentication provider. Key functionalities include an AI-powered chatbot utilizing multiple models via OpenRouter AI, an AI symptom diagnosis tool that generates severity-based assessments, digital health record tracking, automated email reminders through Resend, and a curated educational content module powered by web scraping from trusted sources such as the American Kennel Club (AKC). The application underwent rigorous testing and the results demonstrated high functionality and usability. PawHub successfully bridges the gap between pet owners and virtual veterinary support by providing timely, context-aware guidance, structured health tracking, and expert-backed knowledge. In conclusion, the app proves that AI-enhanced mobile solutions can significantly improve pet care decision-making and owner confidence. Keywords: Artificial Intelligence; Pet Health Management; Symptom Diagnosis; Web Scraping; Pet Care; Mobile Application Subject Area: QA76.75-76.765 Computer software

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