Kennesaw State Researcher Uses Wireless Technology To Improve Soybean Breeding

Detecting crop anomalies early could become easier for farmers thanks to research underway at Kennesaw State University. With support from a $131,863 National Science Foundation (NSF) grant, KSU researchers are developing wireless technology designed to monitor soybean crops and help farmers make more informed decisions. The award is KSU's share of a $660,000 NSF-funded collaboration.

The project, called “SoyWatch,” combines wireless sensors and artificial intelligence to support precision soybean breeding and identify potential threats to crop health, including nutrient deficiencies and disease. Jian Zhang, an associate professor of information technology in KSU's College of Computing and Software Engineering, leads KSU's contribution to the project, collaborating with researchers at the University of Missouri, the University of Memphis, and institutions in India.

Farmers often face challenges monitoring conditions across large areas of farmland. Through SoyWatch, sensors placed in the soil will collect information about growing conditions and transmit the data wirelessly to collection devices mounted on towers, drones, or ground vehicles.

KSU's role focuses on developing a battery-free wireless communication system that can transmit information over longer distances while allowing multiple sensors to communicate simultaneously. The technology is designed to reduce maintenance needs and make large-scale crop monitoring more practical.

“Our goal is to help farmers understand what is happening on their farmland and make better decisions based on the information we collect,” Zhang said. “We want to provide recommendations supported by evidence, so farmers understand not only what actions to take, but why those actions are necessary.”

Once collected, the data will be analyzed using artificial intelligence to provide farmers with recommendations tailored to conditions in their fields.

Although the project focuses on soybeans, Zhang hopes the technology could eventually support other crops, including peanuts grown in Georgia.

This research is supported by the National Science Foundation under Award No. 2549204.