Hackaday Prize Entry: Automated Wildlife Recognition

Trail and wildlife cameras are commonly available nowadays, but the Wild Eye project aims to go beyond simply taking digital snapshots of critters. [Brenda Armour] uses a Raspberry Pi to not only take photos of wildlife who wander into the camera’s field of view, but to also automatically identify and categorize the animals seen using a visual recognition API from IBM via the Node-RED infrastructure. The result is a system that captures an image when motion is detected, sends the image to the visual recognition API, and attempts to identify any wildlife based on the returned data.

The visual recognition isn’t flawless, but a recent proof of concept shows promising results with crows, a cat, and a dog having been successfully identified. Perhaps when the project is ready to move deeper into the woods, elements from these solar-powered networked birdhouses (which also use the Raspberry Pi) could help cut some cords.

11 thoughts on “Hackaday Prize Entry: Automated Wildlife Recognition

      1. Actually I prefer a single feeding station feeder that discriminates around who perches on each electric wired perch and feeding hole. A camera is positioned to get a good profile as to the feeding position. Like the silhouette camera and software to allow cat without mouse treat only to open the cat door featured here. No squirrels, skunk, or birds allowed!

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