Growing Plants on Mars… on Earth

One of the biggest challenges of traveling to Mars is that it’s far away. That might seem obvious, but that comes with its own set of problems when compared to traveling to something relatively close like the Moon. The core issue is weight, and this becomes a big deal when you have to feed several astronauts for months or years. If food could be grown on Mars, however, this would make the trip easier to make. This is exactly the problem that [Clinton] is working on with his Martian terrarium, or “marsarium”.

The first task was to obtain some soil that would be a good analog of Martian soil. Obtaining the real thing was out of the question, as was getting similar dirt from Hawaii. [Clinton] decided to make his own by mixing various compounds from the hardware store in the appropriate amounts. From there he turned to creating the enclosure and filling it with the appropriate atmosphere. Various gas canisters controlled by gas solenoid valves mixed up the analog to Martian atmosphere: 96% dioxide, 2% argon, and 2% nitrogen. The entire experiment was controlled by an Intel Edison with custom circuits for all of the sensors and regulating equipment. Check out the appropriately dramatic video of the process after the break.

While the fern that [Clinton] planted did survive the 30-day experiment in the marsarium, it wasn’t doing too well. There’s an apparent lack of nitrogen in Martian soil which is crucial for plants to survive. Normally this is accomplished when another life form “fixes” nitrogen to the soil, but Mars probably doesn’t have any of that. Future experiments would need something that could do this for the other plants, but [Clinton] notes that he’ll need a larger marsarium for that. And, if you’re not interested in plants or Mars, there are some other interesting ramifications of nitrogen-fixing as well.

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Hackaday Prize Entry: Automatic Digital Microscope

Ziehl-Neelsen Sputum Smear Microscopy (ZN) is one of most common methods for diagnosing Tuberculosis. On the equipment side, it requires not much more than an optical microscope, although it still needs a trained professional to look through the glass, identify and count the number of bacteria in a sample. To provide reliable and effective Tuberculosis diagnostic to regions, where both equipment and trained personnel is in short supply, [Rodrigo Loza] and [khalilnallar] are developing an automated digital microscope based on computer vision and machine learning, their entry for the Hackaday Prize.

automated_microscope_detection_1They started out gathering images of Tuberculosis bacteria from the internet and experimented with color threshold algorithms to detect dyed bacteria, as well as algorithms for counting individual and clusters of bacteria. This process alone can, according to the team, take a trained professional 30 minutes or more. A graphical interface highlights identified bacteria and reads the bacteria count.

[Rodrigo Loza] and [khalilnallar] are testing their device at the Dr. Roberto Galindo Teran hospital in Cobija, Bolivia. However, getting access to a lab environment is one thing, and being given access to a steady supply of fresh M. Tuberculosis samples is another. Unable to obtain samples, which they need to test their algorithms on live subjects, they turned to another front of their project: The hardware. In several iterations, they developed a low-cost, 3D-printable kit, which transforms a laboratory-grade optical microscope into an embedded CNC-controlled microscopy platform. Their kit comprises three stepper-motor-based axis for the X, Y and Z direction, as well as a webcam mount. An Intel Edison and a custom, Arduino compatible shield control the system to achieve features such as homing procedures, autofocus and bacteria detection.

The team is currently in the process of refining their bacteria detection pipeline, exploring the feasibility of semi-automated detection methods, machine learning and neural networks for classification of bacteria within the hardware constraints. The video below shows their latest update on the Z-axis of their microscope.

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Eddie The Balance Bot

Eddie is a surprisingly capable tiny balancing robot based around the Intel Edison from which it takes its name.

Eddie’s frame is 3D printed and comes in camera and top hat editions. The camera edition provides space for a webcam to be mounted, since the Edison has enough go power to do basic vision. The top hat edition just lets you 3D print a tiny top hat for the robot.

The electronics are based around the Edison board and Sparkfun’s set of, “Blocks” designed for it. This project needs the battery block, the H-Bridge block, the GPIO block, and the USB block along with a 9DOF block for balancing. It’s, somewhat unfortunately, not a cheap robot. The motors are Pololu all-metal gearmotors with hall-effect sensors acting as encoders.

We’re really impressed with [diabetemonster]’s design and documentation on the robot. Full source code is provided along with a very nice build guide to get the platform going fast.

There are a few videos of it in action, available after the break. They show it handling situation such as a load being placed on the robot and slopes as well as bonus features like dancing and remote control.

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Puzzle Alarm Clock Gets Couple Up In The Morning

[BrittLiv] and her boyfriend got in one too many fights about who set the alarm. It’s the only argument they seem to repeat. So, true to her nature as an engineer, she over-engineered. The result was this great puzzle alarm clock.

The time displayed on the front is not the current time. Since the argument was about alarm times in the first place, [BrittLiv] decided the most prominent number should be the next alarm. To hear the time a button (one of the dots in the colon) must be pressed on the front of the clock. To set the alarm, however, one must manually move the magnetized segments to the time you’d like to get up. Processing wise, for a clock, it’s carrying some heat. It runs on an Intel Edison, which it uses to synthesize a voice for the time, news, weather, and, presumably, tweets. It sounds great, check it out after the break.

All in all the clock looks great, and works well too. We hope it brought peace to [BrittLiv]’s household.

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Second Skin Synth Fits Like a Glove

California textiles artist and musician [push_reset] challenged herself to make a wearable, gesture-based synth without using flex-sensing resistors. In the end, she designed almost every bit of it from the ground up using conductive fabric, resistive paint, and 3-D printed parts.

A couple of fingers do double duty in this glove. Each of the four fingertips have a sensor made from polyurethane, conductive paint, and conductive fabric that is connected to wires using small rivets. These sensors trigger different samples on an Edison that are generated with Timbre.js. The index and middle fingers also have knuckle actuators made from 3-D printed pin-and-slot mechanisms that turn trimmer pots. Bending one knuckle changes the delay timing while the other manipulates a triangle wave.

On the back of the glove are two sensors made from conductive fabric. Touching one up and down the length will alter the reverb. Sliding up and down the other alters the frequency of a sine wave. [push_reset] has kindly provided everything necessary to re-create this build from the glove pattern to the STL files for the knuckle actuators. Check out a short demonstration of the glove after the break. If you love a parade, here’s a wearable synth that emulates a marching band.

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Smell Colors With A Synesthesia Mask

Synesthesia is a mix-up of sensory perception where stimulation of one sense leads to a stimulation of a second sense. This is the condition where Wednesdays can be blue, the best part of your favorite song can be orange, and six can be up and to the right of seventy-three. While you can’t teach yourself synesthesia – it’s something you’re born with – [Zachary] decided to emulate color to smell synesthesia with his most recent electronics project.

For his synesthesia mask, [Zach] is turning varying amounts of red, green, and blue found with a color sensor into scents. He’s doing this with an off-the-shelf color sensor, an Intel Edison, and a few servos and test tubes filled with essential oils. The color sensor is mounted on a ring, allowing [Zach] to pick which colors he wants to smell, and the scent helmet contains a small electronics box fitted with fans to blow the scent into his face.

There’s more than one type of synesthesia, and if you’re looking for something a little more painful, you can make objects feel loud with a tiny webcam that converts pixels into pulses of a small vibration motor.

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Steering High Altitude Rockets With Cold Gas

Amateur rocketry has been popular for ages, with designs ranging from small toy-scale model rockets to large-scale liquid fuel designs with steerable fins. A team out of Portland State works on some large-scale amateur rockets that can fly to very high altitudes. Since the atmosphere is thin the further the rocket flies, steering fins aren’t incredibly effective once the rockets reach high altitude. A team of students tackled this problem by designing a cold-gas reaction module to steer high-altitude rockets.

The team chose nitrogen as their cold-gas propellant, which is stored in a carbon fiber tank. After passing through a regulator, the gas is routed to several gas solenoids and then to a custom 3d-printed de Laval nozzle. An Intel Edison is used to drive the system, which calculates the rocket’s orientation with a MPU-6050. Control loops use the orientation information and fire gas through any of several nozzle ports to steer the rocket.

The system does have some limits: the solenoids are either on or off, not variable, and they aren’t incredibly fast. Even with these limitations, the team is confident that their module will work great when it embarks on its maiden flight in a brand-new custom rocket next year. The team was also awesome enough to make all of their design files open-source so you can build your own (although they warn that it’s a bit complicated and dangerous). Check out the video after the break to see a test-run of the cold-gas reaction system.

Thanks for the tip, [Nathan]!

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