By Jamie Martin
Up to 40% of global crop production is lost every year to pests, according to the National Institute of Food and Agriculture. In response, a researcher at Kennesaw State University (KSU) is developing an innovative, chemical-free approach to protect strawberry crops using robotics and artificial intelligence.
Assistant professor Taeyeong Choi has created a prototype called MocoBot a low-cost, AI-powered robot designed to patrol strawberry fields at night, identify harmful pests like slugs and snails, and remove them autonomously.
Unlike traditional pest control methods that often rely on widespread pesticide use, MocoBot offers a more sustainable, targeted solution.
MocoBot uses night vision cameras and AI technology to function effectively in low-light conditions, operating during nighttime hours when pests are most active. This unique timing gives farmers a critical advantage in pest control.
“This approach is innovative because it brings AI and robotics into a space where solutions have traditionally relied on chemicals or manual labor,” said Choi, whose project is supported by a Southern Sustainable Agriculture Research and Education grant. “By targeting pests with smart technology, we can help farmers reduce crop loss while protecting the environment.”
Choi emphasized the importance of affordability, particularly for small-scale farmers.
“We realized a lot of farmers can’t afford high-tech robots,” he explained. “We’re committed to keeping MocoBot cost-effective by using inexpensive robotic platforms and simplistic AI models. This, in turn, ensures that performance remains high without requiring costly, high-powered hardware.”
To train the AI, Choi’s team worked closely with local farmers and the KSU Field Station, capturing nighttime images of pests in various conditions to build a robust dataset.
“There’s no existing database of snails and slugs in agricultural environments, especially at night,” Choi noted. “Working with the local farmers has always helped us to expand our research and make a better product.”
MocoBot’s development included a three-step training process: pest identification, robotic pest removal, and safe field navigation. Choi hopes this technology will eventually expand to support other crops and pest types.
“Food security is a growing concern as the global population increases,” Choi said. “By helping farmers reduce pest-related losses without harming the environment, we can make a real difference.”
CCSE Dean Sumanth Yeduri praised the project, calling it “a perfect example of how our faculty are pushing the boundaries of technology to solve real-world problems.”
Categories: National