The Grand Challenges Exploration Initiative (GCI), sponsored by the Bill and Melinda Gates Foundation, recently awarded a UCR computer science graduate student a $100,000 grant to continue her research on insect-classifying sensors.
Yanping Chen, who is working toward a Ph.D. under UCR Professor of Computer Science and Engineering Dr. Eamonn Keogh, won a grant to fine-tune and test the devices she created for classifying and quantifying insect populations.
The initiative funds creative projects that address the world’s most prevalent health-related issues. By soliciting underfunded health research, the organization hopes to find novel and modern solutions to health problems in developing countries worldwide.
Chen built working sensors that can classify species of insects through the sounds given off by the beating of their wings. In turn, she hopes to produce real-time data that can be used to create intervention and suppression plans to fight deadly diseases caused by particular insects.
While at first the study of insects seemed a long way from her undergraduate study of computer science, Chen saw the project as a natural fit, explaining, “Given the importance of insects in human affairs, it is somewhat surprising that computer science has not had a larger impact in entomology.” She added that she spent a considerable amount of time studying the bugs that her lab samples ― a group of 12 insect species.
She did not go into the project alone, however. To build this system of sensors and software, she had some help from Aden Why, an entomology Ph.D. student, and Moses Oben Tataw, who worked under Keogh for his Ph.D. The team created an insectary inside their lab, which housed a population of insects, the majority of which were mosquitoes.
Chen plans to make sensors that are robust and sensitive. Even the simplest alterations to the sensors could have profound effects on the relevancy of the information collected, such as noting the time of day at which the sound is recorded. According to Dr. Keogh, another purpose of the research was “to produce ultra-cheap sensors (less than $3 each) that could be produced in bulk and left unattended anywhere.”
Chen’s system founded real-time information on insect diseases, an addition that she believes is invaluable. There is a “lag time” between when the insect is caught, such as on a sticky trap, and when the insect is counted. Through Chen’s research, this time gap could be greatly diminished and thus, improve disease intervention efforts.
But the applications of her system could extend farther. While insects carry pathogens to human populations, they also wreak havoc on agricultural products. The current system of blanket-spraying crops is expensive, and comes with a host of environmental concerns. Chen explained, “If we can identify insect populations, we can choose to use only the chemicals designed to kill the insects at the locations, and only spray the chemicals in the locations where the insects are present.”
She hopes the information could one day be made available on an open-source, global database where researchers in all fields can utilize the information for their own projects.
