ENHANCING WILDLIFE CONSERVATION AND COMMUNITY RESILIENCE THROUGH AI-BASED BIODIVERSITY MONITORING AND SPATIAL ANALYSIS IN TROPICAL FOREST ECOSYSTEMS

Abstract

 The increasing demand for accurate and accessible biodiversity information has underscored the need for digital technologies that can strengthen wildlife monitoring and conservation initiatives. Responding to this need, this study developed a Digital Photo-Based Faunal Information System for Samar State University (SSU) that unifies artificial intelligence (AI)-supported species recognition, mobile-based field documentation, cloud computing, and Geographic Information System (GIS) technologies into a single biodiversity management platform. Using a developmental research framework, the system was iteratively designed and refined through the Agile software development methodology, encompassing planning, prototyping, implementation, testing, and evaluation. Its capabilities include digital image acquisition of faunal species, automated recording of geospatial and descriptive information, AI-assisted taxonomic identification, and spatial visualization of wildlife observations through an interactive GIS environment. System quality was assessed using the ISO/IEC 9126 software evaluation model, with performance ratings obtained from 60 end users. The evaluation confirmed that the application satisfied the established software quality criteria, achieving mean scores of 4.44 for functionality, 4.39 for usability, 4.32 for reliability, and 4.27 for efficiency. Beyond serving as a digital repository, the platform transforms fragmented biodiversity records into an integrated and searchable ecological database that improves species documentation, facilitates spatial assessment, and supports long-term environmental monitoring. The convergence of AI, GIS, cloud infrastructure, and mobile computing demonstrates the potential of intelligent digital systems to enhance institutional biodiversity management while informing conservation planning, environmental governance, and community resilience strategies for sustainable ecosystem stewardship.