Conservation organisations face significant challenges in monitoring wildlife populations across large areas. Manual analysis of camera trap footage and audio recordings is extremely time-consuming, often taking researchers weeks to process data that accumulates in just days. This creates a bottleneck in conservation efforts, delaying critical decisions about habitat protection and species management.

WildConnect needed a comprehensive platform that could automate species detection from both visual and audio data, provide real-time alerts for rare species sightings, and integrate with existing conservation management systems like EarthRanger whilst maintaining the accuracy required for scientific research.

I built a full-stack wildlife monitoring platform combining modern web technologies with state-of-the-art machine learning models. The system processes camera trap images and bioacoustic recordings automatically, detecting and classifying species with high accuracy whilst providing conservation teams with actionable insights through interactive dashboards and real-time alerts.