Use of Artificial Intelligence for Automated Detection and Surveillance of Red Imported Fire Ants Nests

Abstract

The red imported fire ant, Solenopsis invicta Buren is a destructive invasive species that has spread around the world. Early detection of S. invicta nests is critical for effective monitoring and control in invaded regions. This study presents a novel surveillance system for S. invicta nests combining artificial intelligence and robotic dogs. The system was designed with intelligent recognition algorithms to accurately identify S. invicta nests. With a precision rate of 95%, the system yielded efficient detection of S. invicta nests with increased sensitivity and low missing and false discovery rates, which can aid or even replace humans in locating and delivering pesticides to fire ant nests in open fields to effective control of this invasive pest.