Wildlife Camera Trap AI Image Processing and Management

Managing large wildlife camera studies with 10+ cameras can be difficult and time-consuming without a data management system. Dudek’s AI Image Toolkit (AIT) helps you manage camera trap projects, facilitating faster processing of images collected in the field. Biologists can remotely upload large batches of photos to a cloud-based server. The tool then processes photos in less than half a second, automatically weeding out non-animal photos. Automated processing via AIT is highly cost-effective and efficient, enabling researchers, wildlife camera scientists, and analysts to apply their expertise solely to animal identification and behavior.

Processing Images Faster through Pattern Recognition

AIT is powered by Microsoft’s MegaDetector v5, an artificial neural network that has been trained to identify animals within images. AIT uses pattern recognition to identify images that contain animals and discard those that do not. This automated processing is highly cost-effective and identifies images containing animals with greater than 95% accuracy.

Customized Image Management

Once non-animal images are separated, those containing animals are transferred to a web-based system where users can tag images with various attributes, such as species, gender, age class, behavior, and more. When available, AIT also automatically aggregates photo metadata to populate key attributes such as date, time stamp, environmental conditions, camera settings, etc.

AIT enables collaborative management of projects based on a user’s assigned role.  Users with the data manager role can create projects and locations, as well as configure the overall structure of the project. Taggers can upload images and update their attributes once they have been analyzed. All images are stored at a client-specific, secure, read-only link, and can be retained for as long as the client prefers.

Automated Actionable Data Outputs

AIT provides automatic page summaries for every project, including maps of camera station locations, the number of photos processed, and the number of animal photos. Once images are tagged, they can be searched, sorted, and filtered by species, and more. It is easy to export data from individual sites, as well as across various locations and projects, using additional attributes. Additionally, all data and metadata are organized and can be queried and automatically packaged into formats used in GIS or statistical analysis. Applications include occupancy models, diversity indices, and analyses of the effectiveness of crossing structures.


State Route 62 Wildlife Linkage Study

View the Project

Ready to Du More? Get in touch with our passionate experts.