Poison ivy ranks amongst probably the most medically problematic plants. As much as 50 million people worldwide suffer annually from rashes attributable to contact with the plant, a climbing, woody vine native to america, Canada, Mexico, Bermuda, the Western Bahamas and several other areas in Asia.
It’s found on farms, in woods, landscapes, fields, mountain climbing trails and other open spaces. So, when you go to those places, you are prone to irritation attributable to poison ivy, which may result in reactions that require medical attention. Worse, most individuals do not know poison ivy once they see it.
To search out poison ivy before it finds you, University of Florida scientists published a brand new study by which they use artificial intelligence to verify that an app can discover poison ivy.
Nathan Boyd, a professor of horticultural sciences on the UF/IFAS Gulf Coast Research and Education Center near Tampa, led the research. Renato Herrig, a post-doctoral researcher in Boyd’s lab, designed the app.
“We were the primary to do that, and it was designed as a tool for hikers or others working outdoors,” Boyd said. “The app uses a camera to discover in real-time if poison ivy is present and provides you with a measure of certainty for the detection. It also functions even when you haven’t got connectivity to the web.”
The following step is to make the app commercially available, and there isn’t any timetable for that yet, Boyd said.
For the study, researchers collected hundreds of images of poison ivy from five locations: Alderman’s Ford Conservation Park and Hillsborough River State Park, each in Florida; Eufala National Wildlife Refuge in Alabama; York River State Park in Virgina and Fall Creek Falls State Park in Tennessee.
They labeled images, and in each image, scientists put boxes across the leaves and stems of the plant. The boxed images were critical because poison ivy has a singular leaf arrangement and shape. Scientists use those characteristics to discover the plant.
They then ran the pictures through AI programs and taught a pc to acknowledge which plants are poison ivy. Additionally they included images of plants that will not be poison ivy or plants that seem like poison ivy to make sure the pc learns to differentiate them.
“We imagine that by integrating an object-detection algorithm, public health and plant science, our research can encourage and support further investigations to know poison ivy distribution and minimize health concerns,” Boyd said. Of their future work UF/IFAS researchers hope to expand using the app to discover more noxious plants.
