The University of Texas at Arlington is coordinating a $3.1 million project funded by the U.S. Department of Agriculture to stop the spread of New World screwworm, a flesh-eating parasite threatening livestock across Texas and other states.
New World screwworm was declared eliminated from the United States in 1966 but has recently reemerged, with more than 120 confirmed animal cases reported as of Nov. 12, most of them in Texas, according to the USDA's case dashboard. Female screwworm flies lay eggs in open wounds or mucous membranes of warm-blooded animals; left untreated, the resulting infestations can be fatal.
At the center of the project is an AI-powered "smart trap" capable of distinguishing wild screwworm flies from sterile ones and females from males. Because wild female flies are responsible for producing the destructive larvae, the trap selectively captures them, allowing for earlier detection of potential outbreaks. The technology builds on previous AI-based fruit fly trap research by Shouyi Wang, a UTA associate professor, who expects to have a smart-trap prototype ready by next spring.
Current screwworm traps capture insects indiscriminately, requiring extensive manual sorting and delaying confirmation of the screwworm's presence. They can also interfere with a federal program that releases sterile flies to suppress wild screwworm populations because conventional traps cannot distinguish sterile flies from wild ones.
"This project moves screwworm surveillance beyond today's 'collect first, sort later' trapping methods to AI-driven precision capture," Dr. Wang said. "The smart trap is designed to recognize and selectively retain targeted wild screwworm flies, especially high-risk females, while releasing sterile flies and non-target insects back into the environment. Connected through a smart-trap network, each detection can feed real-time alerts, location-based tracking and predictive risk maps that provide the USDA's Animal and Plant Health Inspection Service (APHIS) with timely, actionable information for faster, more targeted responses."
UTA's project was one of 40 selected nationwide as part of roughly $105 million in USDA funding. UTA will lead overall project coordination and system integration, bringing together a multidisciplinary team of university, industry, government and international partners to move the technology from research prototypes to a field-ready system that can support APHIS and livestock producers. The project runs through June 2028, with fieldwork taking place across multiple states, including Texas, and in affected regions of Mexico.
"Our project aims to develop a real-time surveillance system and AI-enabled on-site diagnostic tools to support producers, veterinary practitioners and government agencies," said Prasanna Gowda, research professor and associate director of UTA's Smart Agriculture Research Center (SARC), which leads the project. "Our proposed AI-enabled diagnostic tools will not only allow producers and veterinary practitioners to identify infections faster but also enable them to report directly to our real-time surveillance system with high-resolution images captured on their smartphones."
Beyond the trap itself, UTA's team will lead development of the AI models that power the smart traps, along with the trap hardware and network, mobile reporting tools and web-based platforms for field reporting. The system will also support data integration, predictive risk forecasting, manufacturing scale-up and large-scale field validation while incorporating targeted chemical lures, portable diagnostic sensors and rapid molecular confirmation to support faster, more targeted responses to potential cases.
"This project is a strong example of how industrial engineering connects AI, optimization, hardware integration and real-world operations," said Sampson Gholston, chair of UTA's Department of Industrial, Manufacturing, and Systems Engineering. "Our faculty are helping move smart technology from the lab toward field-ready deployment for a critical national need."
SARC, established in August 2025, is co-led by Jianzhong Su and Gautam Das and includes more than 20 faculty members from UTA's College of Science and College of Engineering.
"SARC is a premier, one-of-a-kind research hub dedicated to addressing agricultural and natural resource challenges through innovative AI and technology solutions," Dr. Su said. "By harnessing cutting-edge technologies, biological systems and advanced engineering tools, SARC is enhancing food and fiber production in the U.S. This project is a great example of how UTA's strengths in AI and technology enable it to lead this international, multi-institutional team effort to find solutions to meet this complex challenge of nature."
By the end of the project, UTA aims to deliver a complete field-tested system to APHIS for ongoing use in nationwide screwworm surveillance and response.
"Every earlier detection gives producers, veterinarians and animal health officials more time to act," Wang said. "By combining smart traps, field diagnostics, real-time reporting and predictive analytics, this project is designed to turn field data into faster decisions and stronger protection for U.S. agriculture."
About The University of Texas at Arlington (UTA)
The University of Texas at Arlington is a growing public research university in the heart of Dallas-Fort Worth. With a student body of over 42,700, UTA is the second-largest institution in the University of Texas System, offering more than 180 undergraduate and graduate degree programs. Recognized as a Carnegie R-1 university, UTA stands among the nation's top 5% of institutions for research activity. UTA and its 300,000 alumni generate an annual economic impact of $28.8 billion for the state. The University has received the Innovation and Economic Prosperity designation from the Association of Public and Land Grant Universities and has earned recognition for its focus on student access and success, considered key drivers to economic growth and social progress for North Texas and beyond.
