Howdy all ,
It’s great to meet the WildMe Community! My name’s Alan and I’ve been tinkering at Wildlife Warning Sign that focuses on roadside wildlife detection for the purpose of preventing roadkill and also monitoring wildlife activity data via a computer vision based trap camera system in the pursuit of preserving human/wildlife wellbeing. Via multiple infrared sensors and a Microwave radar sensor, the project hopes to detect wildlife presence through changes in the environment heat signatures and depth. Once the sensors have been triggered a NoIR camera snaps a picture of it’s field of vision. Simultaneously, the warning traffic signals also go off. After the picture has been collected, hopefully capturing wildlife in the process, an onboard pre-trained machine learning model runs to identify the said wildlife. The identified wildlife species as well as metadata are incorporated to be mapped for the purpose of identifying regions of dense wildlife activity as well as possible migration patterns.
This project is looking for suggestions and collaboration due to my limited scope on the implementation of artificial intelligence, I was hoping to receive assistance from the community on improving the machine learning capabilities of this project. More specifically, the project is looking to expand on a larger wildlife species prediction capability * (1) and identify migration/animal behavior patterns (2).
(* If you know or are willing to share a database of wildlife images to help improve this project’s machine learning model it would be greatly appreciated! One of the major challenges in helping improve the current wildlife identification model is a lack of available images in model training.)
If there are people interested or willing to, I would love to discuss more deeply the methods used or other ideas on how to improve on the project’s limitations.
Thanks in advance for your time!