Sign In

Communications of the ACM

ACM TechNews

AI, Drones Will Help Pin Down Sosnovsky's Hogweed


View as: Print Mobile App Share: Send by email Share on reddit Share on StumbleUpon Share on Hacker News Share on Tweeter Share on Facebook
Areas in purple were processed by a drone to indicate the presence of Sosnovsky's hogweed.

Scientists at the Skolkovo Institute of Science and Technology have developed an artificial intelligence monitoring system that performs real-time image segmentation onboard drones to identify the presence of Sosnovsky's hogweed.

Credit: Skoltech

To help contain the spread of Sosnovsky's hogweed, a plant hazardous to agriculture, local ecosystems, and human health, across Russia, scientists at the Skolkovo Institute of Science and Technology (Skoltech) have developed an artificial intelligence monitoring system that performs real-time image segmentation onboard drones to identify the toxic weed.

The system uses drones that can capture high-resolution images even in cloudy weather via in-flight data acquisition and processing.

Each drone's computer runs heavy segmentation algorithms based on Fully Convolutional Neural Networks (FCNN) that can identify an irregularly shaped object on a pixel-by-pixel basis.

The researchers utilized popular architectures for the FCNN and adapted them for a single-board computer.

Skoltech's Andrey Somov said, "We installed and flight-tested our monitoring system on board the drone which covered an area of up to 28 hectares in 40 minutes, flying at an altitude of 10 meters. And it did not miss a single weed!"

From Skolkovo Institute of Science and Technology (Russia)
View Full Article

 

Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA


 

No entries found