Advantages:
- Automates mosquito identification, reducing manual inspection efforts.
- Provides immediate species data, aiding timely mosquito control decisions.
- Integrates AI for proactive surveillance and targeted management strategies.
Summary:
Current methods of identifying mosquitoes trapped for research or control purposes are labor-intensive and inefficient. Typically, trapped mosquitoes are manually inspected by experts under microscopes, a process that is time-consuming and requires specialized knowledge. This approach limits the scalability and effectiveness of mosquito surveillance and control efforts worldwide.
Our technology introduces a revolutionary approach to mosquito trapping and identification. By integrating advanced components such as digital microphones, passive infrared sensors, and high-resolution imaging devices, our smart mosquito trap automates the capture of critical data points including wing-beat frequencies and visual images of trapped mosquitoes. This data is processed using AI algorithms developed at our institution, enabling rapid and accurate identification of mosquito genus and species in real-time. This innovation not only enhances the efficiency of mosquito surveillance programs but also provides valuable insights for public health officials and researchers to effectively manage mosquito-borne diseases and ecological studies.
High-resolution images for AI-based mosquito genus classification captured with a smart mosquito trap.
Desired Partnerships:
- License
- Sponsored Research
- Co-Development