This award will enable a team of computer scientists and entomologists at the University of California-Riverside to develop sensors and software that will allow the classification of flying insects. The ability to automatically and accurately classify flying insects has the potential to have significant impact human affairs, because insects spread disease, feed on crops and livestock, and ruin food stores, at a combined annual cost of billions of dollars and incalculable human suffering. Â The intellectual merit of the project is in producing algorithms, devices, and procedures that will radically expand the ability to conduct insect surveillance. Recent advances in sensor technology and machine learning and the ongoing revolution in Big Data are just beginning to enable development of advanced algorithms that will help usher in a new era of computational entomology. The investigators will build inexpensive devices that can detect and classify flying insects. For at least some genera of insects the resulting classification labels will go beyond species-level to predict sex and physiological states (such as virgin vs. gravid and newly emerged vs. mature) of individual insects. The investigators will create computational devices that can determine the origin of selected insects, and selectively capture targeted insects for downstream molecular diagnostic analysis. Producing such information will both accelerate basic research in entomology and will allow more effective vector control. The broader impacts of the project are inherent in the potential to significantly improve the quality and volume of insect surveillance, thus allowing more effective Integrated Vector Management. In the case of mosquitoes, more effective interventions are known to directly save lives. Resulting algorithms will allow the creation of systems to provide actionable information on multiple scales, from informing a policy committee to instructing an agricultural robot to open a valve. The projects comprehensive educational and outreach activities have already been piloted on a small scale and include detailed plans to reach out to underserved communities at the K-12 and college levels.
