New bug sensor saves crops, people
The output of the electronic board is fed into a digital sound recorder and recorded as an MP3 and downloaded to a computer.
The goal is to make this automated classification method as simple, inexpensive and ubiquitous as current methods such as sticky traps and interception traps, but with digital advantages such as higher accuracy, real-time monitoring and the ability to collect additional flight behavior patterns.
In their experiments, the UC Riverside researchers worked with six species of insects. As they added additional insect flight behavior patterns to their classification algorithm, they were able to increase their success classifying the different species.
For example, using only wingbeat sounds they had an 88 percent success rate. When they added time of day the success rate jumped to 95 percent. Then, after adding location, the success rate increased to 97 percent.
The researchers believe that success rate can further be improved by adding additional variables, such as height at which the insects fly and environmental variables such as temperature and humidity.
In a separate experiment, the researchers tested classification accuracy by adding an increasing number of species. With two species, they had 99 percent accuracy. That percentage slowly declined as they added more species. For example, with five species they had a 96 percent accuracy rate and with 10 species it was 79 percent.
The release notes that 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. The 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.
Keogh — who originally developed the sensor with Legos, a 99-cent store laser pointer and a piece from a television remote control — believes the sensors can be built for less than $10 and be powered by solar power or a battery that lasts a year.
In the next year, Keogh, who grew up in Ireland and worked painting carousel horses while attending college in the United States, plans to focus on deploying the sensors around the worldwide. Currently, they are being used on a small scale in Brazil and Hawaii.
Keogh is working with a Tovi Lehmann, an entomologist with the Laboratory of Malaria and Vector Research at the National Institute of Allergy and Infectious Diseases in Rockville, Md., to deploy them in Mali.
The research was supported by the Vodafone Americas Foundation, the Bill and Melinda Gates Foundation, and São Paulo Research Foundation (FAPESP).
— Read more in Yanping Chen et al., “Flying Insect Classification with Inexpensive Sensors,” Journal of Insect Behavior [arXiv:1403.2654 (cs.LG)] (11 March 2014)
