Good news this week from Mars, where Ingenuity finally managed to check in with its controllers after a long silence. The plucky helicopter went silent just after nailing the landing on its 52nd flight back on April 26, and hasn’t been heard from since. Mission planners speculated that Ingenuity, which needs to link to the Perseverance rover to transmit its data, landed in a place where terrain features were blocking line-of-sight between the two. So they weren’t overly concerned about the blackout, but still, one likes to keep in touch with such an irreplaceable asset. The silence was broken last week when Perseverance finally made it to higher ground, allowing the helicopter to link up and dump the data from the last flight. The goal going forward is to keep Ingenuity moving ahead of the rover, acting as a scout for interesting places to explore, which makes it possible that we’ll see more comms blackouts. Ingenuity may be more than ten-fold over the number of flights that were planned, but that doesn’t mean it’s ready for retirement quite yet.
Much of the reporting around climate change focuses on carbon dioxide. It’s public enemy number one when it comes to gases that warm the atmosphere, as a primary byproduct of fossil fuel combustion.
It’s not the only greenhouse gas out there, though. Methane itself is a particularly potent pollutant, and one that is being emitted in altogether excessive amounts. Satellites are now on the hunt for methane emissions in an attempt to save the world from this odorless, colorless gas.
Historically, nature has used trees to turn carbon dioxide back into oxygen for use by living creatures. The trees play a vital role in the carbon cycle, and have done so for millennia. Recently, humans have thrown things off a bit by getting rid of lots of trees and digging up a lot more carbon.
While great efforts are underway to replenish the world’s tree stocks, Belgrade has gone in a different direction, creating artificial “liquid trees” to capture carbon dioxide instead. This has spawned wild cries of dystopia and that the devices are an affront to nature. Let’s sidestep the hysteria and look at what’s actually going on.
If there’s one thing that never seems to suffer from supply chain problems, it’s litter. It’s everywhere, easy to spot and — you’d think — pick up. Sadly, most of us seem to treat litter as somebody else’s problem, but with something like this machine vision litter mapper, you can at least be part of the solution.
For the civic-minded [Nathaniel Felleke], the litter problem in his native San Diego was getting to be too much. He reasoned that a map of where the trash is located could help municipal crews with cleanup, so he set about building a system to search for trash automatically. Using Edge Impulse and a collection of roadside images captured from a variety of sources, he built a model for recognizing trash. To find the garbage, a webcam with a car window mount captures images while driving, and a Raspberry Pi 4 runs the model and looks for garbage. When roadside litter is found, the Pi uses a Blues Wireless Notecard to send the GPS location of the rubbish to a cloud database via its cellular modem.
Cruising around the streets of San Diego, [Nathaniel]’s system builds up a database of garbage hotspots. From there, it’s pretty straightforward to pull the data and overlay it on Google Maps to create a heatmap of where the garbage lies. The video below shows his system in action.
Yes, driving around a personal vehicle specifically to spot litter is just adding more waste to the mix, but you’d imagine putting something like this on municipal vehicles that are already driving around cities anyway. Either way, we picked up some neat tips, especially those wireless IoT cards. We’ve seen them used before, but [Nathaniel]’s project gives us a path forward on some ideas we’ve had kicking around for a while.
For some reason, wildfire seasons in Australia, North America, and other places around the world seem to happen more and more frequently and with greater and greater fervor. Living in these areas requires special precautions, even for those who live far away from the fires. If you’re not sure if the wildfires are impacting your area or not, one of the tools you can build on your own is an air quality meter like [Costas Vav] shows us in this latest build.
The air quality indicator is based around an Adafruit Feather RP2040 which is in turn based on the 32-bit Cortex M0+ dual core processor. This makes for a quite capable processor in a small package, and helps accomplish one of the design goals of a rapid startup time. Another design goal was to use off-the-shelf components so that anyone could easily build one for themselves, so while the Feather is easily obtained the PMS5003 PM2.5 air quality sensor needed to be as well. From there, all of the components are wrapped up in an easily-printed enclosure and given a small (and also readily-available) OLED screen.
[Costas Vav] has made all of the files needed to build one of these available, from the bill of materials to the software running on the Pi-compatible board to the case designs. It’s a valuable piece of technology to have around even if you don’t live in fire-prone areas. Not only can wildfire smoke travel across entire continents but simple household activities such as cooking (especially with natural gas or propane) can decimate indoor air quality. You can see that for yourself with an army of ESP32-based air quality sensors.
According to [Dr. Tom Lehrer’s] song Pollution, “Wear a gas mask and a veil. Then you can breathe, long as you don’t inhale!” While the air quality in most of the world hasn’t gotten that bad, there is a lot of concern about long-term exposure to particulates in the air causing health problems. [Ashish Choudhary] married an Arduino with a display and a pollution sensor to give readings of the PM2.5 and PM10 levels in the air.
The sensor uses a laser diode and a photodiode to detect and count particles, while a fan moves air through the system. If you aren’t up on pollution metrics, PM2.5 is a count of very fine particles (under 2.5 microns) and PM10 is a count of particles for 10 microns. You can find a datasheet for the device online.
There’s a laundry list of ways that humans are polluting the earth, and even though it might not look like it from the surface, the oceans seem to bear the brunt of our waste. Some research suggests that plastic doesn’t fully degrade as it ages, but instead breaks down into smaller and smaller bits that will be somewhere the in environment for such a long time it could be characterized in layman’s terms as forever.
Not only does waste of all kinds make its way to the oceans by rivers or simply by outright dumping, but commercial fishing gear is estimated to comprise around 10% of the waste in the great blue seas, and one of the four nonprofits help guide this year’s Hackaday Prize is looking to eliminate some of that waste and ensure it doesn’t cause other problems for marine life. This was the challenge for the Conservation X Labs dream team, three people who were each awarded a $6,000 micro-grant to work full time for two months on the problem.
It isn’t about simply collecting waste in the ocean, but rather about limiting the time that potentially harmful but necessary fishing equipment is in the water in the first place. For this two-month challenge, this team focused on long lines used by professional fishing operations to attach buoys to gear like lobster pots or crab traps. These ropes are a danger to large ocean animals such as whales when they get tangled in them and, if the lines detach from the traps, the traps themselves continue to trap and kill marine life for as long as they are lost underwater. This “ghost gear” is harmful in many different ways, and reducing its time in the water or “soak time” was the goal for the project.
Let’s take a closer look at their work after the break, and we can also see the video report they filed as the project wrapped up.