Air pollutants known as particulate matter are a complex mixture of microscopic solids and liquid droplets with some particles—such as dust, dirt, soot or smoke—large enough or dark enough to be seen with the naked eye. Other particulates are so small they can only be detected using an electron microscope. Now researchers are expanding their ability to study even the smallest particulates using unmanned aircraft systems (UAS) to carry such instruments into the sky and analyze what is in the air we breathe.
Once inhaled, particulate matter can damage the lungs and heart and cause serious health effects, “even cancer,” said Aydogan Ozcan, a professor of electrical and computer engineering and bioengineering at the University of California, Los Angeles.
Ozcan’s lab has long worked on imaging techniques for environmental applications. Their research yielded novel lens-less microscopes, where samples are directly placed over imaging chips with no optical components between them for compact, high-throughput and cost-effective imaging, Ozcan said.
Current monitoring techniques for aerosols of this particulate matter “are either bulky or low-throughput,” Ozcan said. For instance, air sampling stations typically use beta-attenuation monitoring or tapered element oscillating microbalance instruments that usually weigh roughly 30 kilograms, cost about $50,000 to $100,000, and require specialized personnel or technicians for regular system maintenance every few weeks. Although commercially available, portable particle counters only cost roughly $2,000 to $8,000, they sample the air at rates of less than 2 to 3 liters per minute, and accurate measurements of either very-high or very-low concentrations of particles is challenging for these devices. Moreover, neither of these options provides microscopic images of captured particulate matter for detailed analysis, Ozcan added.
“We thought this very light-weight and versatile microscope platform would be a good fit as a payload for a drone to perform three-dimensional air quality monitoring—to see the particles in air that people do not normally see with their bare eyes,” Ozcan said.
Airborne Microscopes
In the beginning, Ozcan said, he and his lab had no experience with drones.
“A major effort of ours for this application with drones was to reduce the weight of the device so we can fit it into a smaller, more portable and cheaper drone,” he told Inside Unmanned Systems.
Their efforts have resulted in a mobile imaging system they call c-Air. “So far the c-Air device weighs about 600 grams,” Ozcan said.
The device can screen 13 liters of air per minute and generates microscopic images of scanned particulate matter, providing statistics of particle size and density distribution with a sizing accuracy of roughly 93 percent. They also integrated the device with a smartphone application to control c-Air and display results.
The device relies on cloud computing to remotely, rapidly and accurately analyze acquired images of particulate matter. Artificial-intelligence machine-learning algorithms can be used, said Ozcan and his colleagues, to adaptively tailor c-Air to identify specific particles in the air, such as various types of pollen and mold. It won the Vodafone Wireless Innovation Project prize in 2016.
The device uses a pump to drive air into a nozzle, inside which particulate matter can latch onto a sticky coverslip. Red, green and blue LEDs then illuminate this coverslip so a color CMOS (complementary metal-oxide semiconductor) image sensor—the same kind used in most digital cameras—can take pictures of the particles from a distance of just 400 microns, a span about four times the average width of a human hair.
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