Florida Researchers Deploy AI-Powered Mosquito Trap with 98% Accuracy to Combat Dengue Outbreaks

AI-Powered Mosquito Trap Addresses Florida's Dengue Crisis

As Florida confronts one of its most severe dengue outbreaks in nearly a century, with over 700 cases reported as of October 22, researchers at the University of South Florida have developed an AI-powered mosquito trap that could transform how public health officials combat mosquito-borne diseases2

2

. The technology, created by Associate Professor Ryan Carney and Professor Sriram Chellappan and commercialized through USF startup Digitomy, has demonstrated over 98% accuracy in identifying mosquito species during laboratory testing1

1

. This development matters because traditional mosquito surveillance requires specialists to spend two to three days examining specimens under microscopes, delaying critical interventions during active outbreaks1

1

.

How the Smart Trap Identifies Dengue-Carrying Mosquitoes

The AI-powered mosquito trap operates by hanging from low tree branches or sitting on the ground, using either light or bait to attract insects while a fan draws them inside onto a sticky pad1

1

. Two built-in cameras photograph the captured mosquitoes, allowing the artificial intelligence to identify species, gender, and whether they have fed on blood by matching images against a vast database1

1

. The system proves remarkably energy-efficient, requiring less power to analyze an entire sticky pad of mosquitoes than sharing a single Instagram post2

2

. Carney emphasized the trap's strategic importance: "While there are 3,500 mosquito species, it's primarily only one, Aedes aegypti, that is spreading dengue in Florida. We can use the data from our smart traps to construct a habitat model, as well as to monitor the species' presence and abundance in real time, to strategically mitigate its spread"1

1

.

Real-Time Data Transforms Disease Surveillance

Digitomy's technology integrates cloud computing and a mapping dashboard to provide public health officials with same-day results, a stark contrast to the multi-day delays of conventional methods1

1

. The trap data feeds into a private layer of Digitomy's Global Mosquito Observations Dashboard, which combines information from smart traps with more than half a million citizen science reports1

1

. This real-time data enables mosquito control districts to pinpoint where disease-carrying species concentrate and direct targeted interventions more effectively2

2

. The system could eventually complement Carney's earlier DYCAST early warning system for dengue outbreaks and West Nile virus1

1

. Rui-De Xue, executive director of Anastasia Mosquito Control District, noted that "collaborating with Digitomy and USF will benefit our programs by helping us explore and adopt new artificial intelligence technology"1

1

.

Public Education Platform Enhances Mosquito Species Identification

Beyond surveillance, Digitomy is developing a cloud-based education platform for both mosquito control professionals and the general public1

1

. Users can examine mosquito images, identify species, and receive AI-generated feedback to improve their mosquito species identification skills without attending in-person training sessions2

2

. Carney stressed the importance of community engagement: "Education is our secondary line of defense. While our smart traps provide the macro-level data, the public should practice the three D's: Drain standing water, Dress to cover skin and wear DEET"1

1

. The researchers plan to integrate this platform into professional training programs with mosquito control districts, including Anastasia and Hillsborough1

1

.

Strategic Mitigation of Dengue Through Technology Licensing

As Digitomy prepares for field validation with Hillsborough County and consumer sales, the team is working with USF's Technology Transfer office to license the technology to established mosquito trap manufacturers1

1

. This approach would combine existing equipment with USF's AI identification system, potentially accelerating deployment across regions facing mosquito-borne diseases. Diana Shapiro, chief operations officer of Digitomy, explained the urgency: "Mosquito-control programs wait days to learn what is in their traps. Our technology is built to tell them the same day, and to reach the places with the least to spend and the most at stake"1

1

. Research behind Digitomy has been underway at the University of South Florida since 2018, with testing at USF and partnerships with St. Johns County's Anastasia Mosquito Control District helping advance the technology1

1

. The short-term impact centers on Florida's immediate outbreak response, while long-term implications suggest this AI-driven approach could establish new standards for global disease surveillance, particularly in resource-limited regions where mosquito-borne diseases pose the greatest threat.