Stray Love: Animal Adoption System

Abstract

The Animal Adoption System is a digital platform developed to simplify and promote the adoption of stray and abandoned animals through a mobile application. The system enables users to explore available animals, view detailed profiles, and send adoption requests directly to registered shelters. This approach minimizes manual efforts, encourages adoption awareness, and ensures transparency in the overall process. The project is implemented using Flutter, which allows cross-platform development for Android and iOS devices, and Firebase, which offers real-time database, authentication, and cloud storage services. The system bridges the gap between potential adopters and shelter organizations, promoting a structured and efficient adoption environment. In addition, the system enhances user trust through secure authentication, data integrity, and real-time notifications. Evaluation results demonstrate the platform’s scalability and responsiveness. This paper highlights the motivation, architecture, methodology, and experimental evaluation of the system, showcasing how digital transformation can improve animal welfare initiatives.

Introduction

The increasing population of stray and abandoned animals in India poses challenges for both public safety and animal welfare. Traditional adoption processes are manual, fragmented, and localized, leading to inefficiencies and fewer successful adoptions. The Animal Adoption System addresses these issues by providing a centralized, mobile-friendly platform built with Flutter and Firebase, connecting shelters with potential adopters in real time.

The system features a User Module for browsing animals and submitting adoption requests, an Admin Module for verifying listings and approving adoptions, and a Database Module using Firebase Firestore for secure, cloud-based storage. Real-time notifications, image uploads, and access control ensure transparency, convenience, and data security.

By integrating mobile technology and cloud services, the platform overcomes limitations of previous web-centric solutions, enabling efficient, scalable, and accessible adoption processes. Its modular design also allows for future enhancements, such as AI-based breed recognition or chatbots, providing a flexible and robust tool for improving animal welfare and promoting responsible pet adoption.

Conclusion

The proposed Animal Adoption System successfully integrates modern mobile and cloud technologies to support animal welfare. By digitizing the adoption process, it bridges the communication gap between adopters and shelters, ensuring trust, security, and transparency. The system was implemented and tested successfully, confirming its reliability and efficiency for real-world deployment. The project demonstrates how a technical approach can bring meaningful social impact. By offering real-time data and intuitive navigation, it promotes responsible pet ownership and increases adoption rates. In future work, the system can be enhanced with AI-based features such as automatic animal breed identification, personality matching between adopter and pet, and post-adoption health tracking. Integrating chat functionality and veterinary service connections would further enrich the user experience. Thus, the Animal Adoption System stands as a scalable, efficient, and socially beneficial solution that demonstrates how digital innovation can be utilized to address one of society’s most pressing welfare challenges.

References

[1] S. Patel, “Pet Adoption Platform Using Mobile Technology,” International Journal of Computer Applications, vol. 175, no. 12, 2021. [2] M. Singh and R. Sharma, “Cloud-Based Pet Management System,” International Journal of Emerging Technologies, 2022. [3] Google Developers, “Flutter Documentation,” Available at: https://flutter.dev [4] Firebase Documentation, “Firebase for Android,” Available at: https://firebase.google.com [5] Becerra, Z. M., Parmar, S., May, K., & Stuck, R. E. “Exploring User Information Needs in Online Pet Adoption Profiles,” Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 64(1), 1308–1312, 2020.

Copyright

Copyright © 2025 Neha Mahendra Chaudhari, Shruti Milind Jagtap, Prof. Divya Rahane . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.