Aplicación móvil para la gestión de adopciones y reporte de mascotas extraviadas con generación de imágenes mediante IA en la Fundación Huellitas

Abstract

Animal abandonment and overpopulation place sustained pressure on rescue organizations that still rely on manual procedures. At the Fundacion Huellitas, information about available animals was scattered across social media, paper records reached occupancy near ninety percent, search filters were absent, and adopter evaluation depended on manual judgment without digital validation. This fragmentation limited adoption campaigns and weakened the adopter experience. The study aimed to develop a mobile application that facilitates the adoption of stray animals and improves user experience within the foundation. A field and applied research approach combined surveys with potential adopters and interviews with foundation staff to define functional and non-functional requirements. The application was developed under the Rapid Application Development methodology across its four phases, using React Native with Expo, Cloud Firestore, Firebase Authentication, Storage, Cloud Messaging, and Cloud Functions as an intermediary layer toward the Gemini image-generation model. The system integrated four independent modules: adoption, lost pets, generative artificial intelligence, and administration. Acceptance testing across four iterations on a physical Android device verified twenty-six functional and non-functional criterio with full compliance. Usability was measured through the System Usability Scale applied to twelve potential adopters who first completed five representative tasks, yielding a mean of 80.21 and a standard deviation of 4.05. Every participant exceded the industry benchmark of sixty-eight points, and 66.7 % reached the good-usability threshold. The findings confirm that the application improved the adopter experience over the previous manual process and offer a scalable basis for future animal-welfare features.