Since 2007, IRC has been using a network of over 50 strategically placed heat- and motion-triggered remote cameras throughout the Landmarks to monitor the health and activity of wildlife. Images captured by the camera traps provide vital information about the health and activity of wildlife in correlation with human activity on the land. However, this project has always been limited by technology and the time it takes to process the thousands of images captured on the camera traps.
IRC teamed up with Microsoft to combat this problem. Microsoft’s AI and machine learning software, MegaDetector, can be applied to detect wildlife in the images so that less time is spent sifting through “false trigger” photos. The software is trained with local camera trap data to recognize when either an animal, vehicle, or human passes through and then automatically tag these photos. To access the increased computing power necessary to run this program, IRC was awarded an AI for Earth grant from Microsoft.
With the new AI software, staff will be able to spend more time processing and analyzing data instead of logging data, which will help IRC and its partners focus on higher level research and take better care of the land. As more new technologies become available, IRC hopes to explore camera technology that can capture a larger range of smaller animals, as traditional wildlife cameras are generally set up to capture bigger animals that have more prominent heat signatures and make more movement.
For more information about wildlife monitoring on the Landmarks, visit IRConservancy.org or follow the Landmarks on Facebook, Instagram and Twitter.