Bug sensorsNew bug sensor saves crops, people
For hundreds of years humans have attempted to kill unwanted insects. While some blanket methods have been successful, they can be costly and create environmental problems. A new sensor developed by UC Riverside researchers aims to change that by counting and classifying the insects so that the substance used to eradicate the harmful insects can be applied on a precision targeted level. The inexpensive wireless sensors have 99 percent accuracy, and they are expected to have applications fighting insect-borne diseases, such as malaria, and insects that damage crops.
UC Riverside, at the heart of new insect identfication system // Source: ucr.edu
University of California, Riverside researchers have created a method that can classify different species of insects with up to 99 percent accuracy, a development that could help farmers protect their crops from insect damage and limit the spread of insect-borne diseases, such as malaria and Dengue fever.
Over the past sixty years, insect classification research has been limited by factors including an overreliance on acoustic sensing devices, a heavy focus on wingbeat frequency and limited data.
A UC Davis release reports that the UC Riverside researchers overcame those limitations by building an inexpensive wireless bug sensor that can track many insect flight behavior patterns and generate much larger amounts of data that can then be incorporated into classification algorithms.
In about three years, by having dozens of sensors running in parallel twenty-four hours a day, the UC Riverside researchers have collected tens of millions of data points, more than all previous work in this field combined.
“We set out not knowing what was possible,” said Eamonn Keogh, a computer science professor at UC Riverside’s Bourns College of Engineering. “Now, the problem is essentially solved. We have created insect classification tools that can outperform the world’s top entomologists in a fraction of the time.”
The research findings are under review for publication in an upcoming issue of the Journal of Insect Behavior. Keogh’s co-authors are: Yanping Chen, a computer science graduate student at UC Riverside (the lead author); Adena Why, an entomology graduate student at UC Riverside; Gustavo Batista, of the University of Sao Paulo in Brazil; and Agenor Mafra-Neto, of ISCA Technologies in Riverside.
Filled with tables, chairs and computers, Keogh’s lab at the University of California, Riverside Bourns College of Engineering looks like many computer science labs.
Open the closet door, however, and there are a couple dozen shoebox-size plastic containers from a local pet store, each filled with up to 100 insects and connected to an optical sensor. The sensor consists of a phototransistor array, which is connected to an electronic board and a laser pointing at the phototransistor array.
When the insect passes across the laser beam, its wings partially block the light, causing a small light fluctuation. The fluctuations are captured by the phototransistor array as changes in current, the signal is then filtered and amplified by the custom designed electronic board.
