Radar Can Tell the Difference Between Insect Species
European researchers built a radar system that can tell the difference between insect species, offering a possible cost-effective, noninvasive way to monitor pollinators such as bees. The system uses millimeter-wave radar to capture micro-Doppler signatures from insect wingbeats, then a machine learning model classifies the species. In tests, the model identified five pollinator species to the species level with 85 percent accuracy.
Key Takeaways
- Bees and other pollinating insects play vital roles in food webs and crop pollination, yet monitoring them has proved difficult.
That's why researchers have developed a radar system that could lead to a cost-effective, noninvasive way to track pollinators.
- It's not a new idea-scientists have used radar for decades to study migratory insects.
However, that research was mostly focused on insects flying in large numbers at high altitudes, instead of lone insects flying near the ground, as pollinators do when visiting flowers.
- Millimeter-Wave Radar for Pollinators The scientists opted for millimeter waves for their radar system, because those wavelengths better match insect sizes than other portions of the radio-frequency spectrum.
Millimeter waves have also found use in recent generations of cellular networks .
- These included not only wingbeat frequencies but also the speed at which insect wing movements changed and the strength of the reflections.
The researchers detailed their findings on 28 April in the journal PNAS Nexus .
- When it came to more broadly distinguishing between the four bee species and the one wasp species-two different families of insects-it was able to do so with 96 percent accuracy.
Stats & Key Facts
- #In tests, the model identified five pollinator species to the species level with 85 percent accuracy.
- #The scientists had their model analyze more than 70 different features of the radar reflections from the insects.
- #The model was able to classify the five kinds of insects to the species level with 85 percent accuracy.
- #When it came to more broadly distinguishing between the four bee species and the one wasp species-two different families of insects-it was able to do so with 96 percent accuracy.
Bees and other pollinating insects play vital roles in food webs and crop pollination, yet monitoring them has proved difficult. That's why researchers have developed a radar system that could lead to a cost-effective, noninvasive way to track pollinators. Traditionally, identifying pollinators has proven tricky and time-consuming, and typically requires capturing and killing insects to get a close look at them.
To find a better way to monitor pollinators , scientists are developing vision systems that use machine learning to automatically classify insects. However, these machine learning systems face a major limitation when acquiring usable images, because of issues such as variable lighting, poor weather, and cluttered backgrounds-not to mention that many insects can just fly away when approached. That's why researchers based in Europe instead analyzed radar scans of insects.
It's not a new idea-scientists have used radar for decades to study migratory insects. However, that research was mostly focused on insects flying in large numbers at high altitudes, instead of lone insects flying near the ground, as pollinators do when visiting flowers. "Typically, the radar reflection from single insects is very weak," says Adam Narbudowicz , an associate professor of space research and technology at the Technological University of Denmark.
For more details please read the original article at IEEE Spectrum AI.
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