Optimizing the Accuracy and Efficiency of Camera Trap Image Analysis: Evaluating AI Model Performance and a Semi-Automated Workflow
Abstract
The widespread adoption of camera trap surveys for wildlife monitoring has generated a substantial volume of ecological data, yet processing constraints persist due to the time-consuming process of manual image classification and the reliability of automated systems. This study assesses the performance of Conservation AI’s UK Mammals model in classifying three species—Western European hedgehogs (Erinaceus europaeus), red foxes (Vulpes vulpes), and European badgers (Meles meles)—from a subsample of 234 records from camera trap images collected through a citizen science initiative across residential gardens. This analysis was repeated after retraining the model to assess improvement in model performance. Initial model outputs demonstrated high precision (>0.80) for foxes and hedgehogs but low recall (
Fields of Study & Subjects
Wildlife Ecology and Conservation
Species Distribution and Climate Change
Environmental DNA in Biodiversity Studies
Publication details
- Journal / source
- Remote Sensing
- Publisher
- MDPI AG
- Volume
- 18
- Issue
- 3
- Pages
- 502–502
- Publication date
- 4 February 2026
- Language
- EN