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#437585 Dart-Shooting Drone Attacks Trees for ...
We all know how robots are great at going to places where you can’t (or shouldn’t) send a human. We also know how robots are great at doing repetitive tasks. These characteristics have the potential to make robots ideal for setting up wireless sensor networks in hazardous environments—that is, they could deploy a whole bunch of self-contained sensor nodes that create a network that can monitor a very large area for a very long time.
When it comes to using drones to set up sensor networks, you’ve generally got two options: A drone that just drops sensors on the ground (easy but inaccurate and limited locations), or using a drone with some sort of manipulator on it to stick sensors in specific places (complicated and risky). A third option, under development by researchers at Imperial College London’s Aerial Robotics Lab, provides the accuracy of direct contact with the safety and ease of use of passive dropping by instead using the drone as a launching platform for laser-aimed, sensor-equipped darts.
These darts (which the researchers refer to as aerodynamically stabilized, spine-equipped sensor pods) can embed themselves in relatively soft targets from up to 4 meters away with an accuracy of about 10 centimeters after being fired from a spring-loaded launcher. They’re not quite as accurate as a drone with a manipulator, but it’s pretty good, and the drone can maintain a safe distance from the surface that it’s trying to add a sensor to. Obviously, the spine is only going to work on things like wood, but the researchers point out that there are plenty of attachment mechanisms that could be used, including magnets, adhesives, chemical bonding, or microspines.
Indoor tests using magnets showed the system to be quite reliable, but at close range (within a meter of the target) the darts sometimes bounced off rather than sticking. From between 1 and 4 meters away, the darts stuck between 90 and 100 percent of the time. Initial outdoor tests were also successful, although the system was under manual control. The researchers say that “regular and safe operations should be carried out autonomously,” which, yeah, you’d just have to deal with all of the extra sensing and hardware required to autonomously fly beneath the canopy of a forest. That’s happening next, as the researchers plan to add “vision state estimation and positioning, as well as a depth sensor” to avoid some trees and fire sensors into others.
And if all of that goes well, they’ll consider trying to get each drone to carry multiple darts. Look out, trees: You’re about to be pierced for science.
“Unmanned Aerial Sensor Placement for Cluttered Environments,” by André Farinha, Raphael Zufferey, Peter Zheng, Sophie F. Armanini, and Mirko Kovac from Imperial College London, was published in IEEE Robotics and Automation Letters.
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#437554 Ending the COVID-19 Pandemic
Photo: F.J. Jimenez/Getty Images
The approach of a new year is always a time to take stock and be hopeful. This year, though, reflection and hope are more than de rigueur—they’re rejuvenating. We’re coming off a year in which doctors, engineers, and scientists took on the most dire public threat in decades, and in the new year we’ll see the greatest results of those global efforts. COVID-19 vaccines are just months away, and biomedical testing is being revolutionized.
At IEEE Spectrum we focus on the high-tech solutions: Can artificial intelligence (AI) be used to diagnose COVID-19 using cough recordings? Can mathematical modeling determine whether preventive measures against COVID-19 work? Can big data and AI provide accurate pandemic forecasting?
Consider our story “AI Recognizes COVID-19 in the Sound of a Cough,” reported by Megan Scudellari in our Human OS blog. Using a cellphone-recorded cough, machine-learning models can now detect coronavirus with 90 percent accuracy, even in people with no symptoms. It’s a remarkable research milestone. This AI model sifts through hundreds of factors to distinguish the COVID-19 cough from those of bronchitis, whooping cough, and asthma.
But while such high-tech triumphs give us hope, the no-tech solutions are mostly what we have to work with. Soon, as our Numbers Don’t Lie columnist, Vaclav Smil, pointed out in a recent email, we will have near-instantaneous home testing, and we will have an ability to use big data to crunch every move and every outbreak. But we are nowhere near that yet. So let’s use, as he says, some old-fashioned kindergarten epidemiology, the no-tech measures, while we work to get there:
Masks: Wear them. If we all did so, we could cut transmission by two-thirds, perhaps even 80 percent.
Hands: Wash them.
Social distancing: If we could all stay home for two weeks, we could see enormous declines in COVID-19 transmission.
These are all time-tested solutions, proven effective ages ago in countless outbreaks of diseases including typhoid and cholera. They’re inexpensive and easy to prescribe, and the regimens are easy to follow.
The conflict between public health and individual rights and privacy, however, is less easy to resolve. Even during the pandemic of 1918–19, there was widespread resistance to mask wearing and social distancing. Fifty million people died—675,000 in the United States alone. Today, we are up to 240,000 deaths in the United States, and the end is not in sight. Antiflu measures were framed in 1918 as a way to protect the troops fighting in World War I, and people who refused to wear masks were called out as “dangerous slackers.” There was a world war, and yet it was still hard to convince people of the need for even such simple measures.
Personally, I have found the resistance to these easy fixes startling. I wouldn’t want maskless, gloveless doctors taking me through a surgical procedure. Or waltzing in from lunch without washing their hands. I’m sure you wouldn’t, either.
Science-based medicine has been one of the world’s greatest and most fundamental advances. In recent years, it has been turbocharged by breakthroughs in genetics technologies, advanced materials, high-tech diagnostics, and implants and other electronics-based interventions. Such leaps have already saved untold lives, but there’s much more to be done. And there will be many more pandemics ahead for humanity.
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