While members of the Oshman Engineering Design Kitchen makerspace at Rice University generally do a good job with wearing proper eye protection and gloves, hearing safety has lagged behind. In order to make it obvious when students need to apply the protective equipment, the “Ring the Decibels” team there has come up with an excellent sound display, laser cut out of wood and acrylic.

Their system uses an analog sound sensor to detect noise passing data on to an Arduino Uno. In response, the Uno controls two LED strips, one of which indicates levels in the form of a VU meter, while the second strip flashes red under an acrylic headphones cutout when dangerous levels are present. 

Build details are available here, and you can check out the demo below to see how it works! 

LEDs are fun, and RGB(W)s adds a new element to things, but what if you want a light that can also move by itself? The Mover3D does just that as a pan/tilt system controlled by the DMX512 communication protocol. You simply feed instructions in via any standard lighting console, and it dances around under your commands.

The 3D-printed device uses an Arduino Uno inside the fixture’s base to send signals to an RGBW LED, as well as control a pair of servo motors that pan and tilt the light turret. While light output is limited for now, a second version featuring a 14,000 lumen output with stepper motors and slip rings for 360° rotation is in the works, and should be quite impressive when it’s done! 

Setup and programming instructions can be found in the project’s write-up, and needed print files are up on Thingiverse.

Richard J. Prinz wasn’t satisfied with pickable physical locks, so he decided to see if he could instead secure physical things with his YubiKey USB security fob.

His setup uses an Arduino Uno, along with a USB host shield, to read data from the YubiKey then compare it to a stored password or passwords. If the proper code is submitted by the fob, it then unlocks the door, vault, chain, or any other security device, here represented by a green LED.

While the build shown is a breadboard-based prototype, it fulfills the basic goal of creating a standalone physical USB security platform. If you’d like to create something similar, or perhaps integrate the concept into an actual physical lock, code is available on GitHub[2].

When you want to build a walking robot, the normal route is to individually control each leg with a number of servos or other actuators. Maker Jeremy S. Cook, however, took a different approach with his ‘ClearCrawler,’ using only a pair of motors to power eight legs. These legs are divided up into sets of four on either side of the bot, allowing for differential control similar to a tank.

The leg linkage design is based on Theo Jansen’s Strandbeest mechanism, and a clear head is also implemented with a pair of 8×8 MAX7219 LED matrix eyes. Onboard control is handled by an Arduino Nano and an L298N driver board, while an Uno with a joystick shield serves as the user interface. Radio transmission is via two nRF24L01 modules.

Code for both the transmitter and receiver can be found on GitHub.

Inventor Artist Darcy Whyte wanted a drawing robot that was light enough to carry around, and could quickly produce drawings. Naturally, he turned to an Arduino Uno, along with a CNC shield and a trio of A4988 stepper drivers. These control a NEMA 8 and two NEMA17 stepper motors in a gantry-style artistic setup.

The build is able to drag a marker across a page, apparently varying pressure applied with the z-axis, and thus how much ink is applied. In another mode, a pen can be used, which wobbles back and forth to create volume when needed. 

Both methods, as seen in the clips below, can sketch a very recognizable—though certainly distinct—portrait of Marilyn Monroe, or presumably whatever other image you choose to program in.

If Elon Musk was to design a soapbox car, the prototype might look something like this by David Traum.

Traum’s project is powered by a 500W motor which is fed by a pair of 12V batteries and a 40 W solar cell, allowing it to attain a top speed of 35 km/h and a range of 10 to 15km. Although that might not sound like a huge number, it looks pretty fast at the end of the video below!

But that’s not all. The vehicle features a rather unique control system, with front wheel steering actuated by a stepper and cable assembly. An Arduino Mega is the brains of the operation, while user input is via a small touchscreen, a joystick, and even a steering wheel (equipped with an Uno, a 9V battery, radio module, and gyro sensor) that can work wirelessly as needed—perhaps to park remotely, or simply as a gigantic RC car

The clip here is in German, but you can read more in this English-translated article.

Imagine if you had whiskers. Obviously, this would make you something of an oddity in today’s society. On the other hand, you’d be able to sense nearby objects via the transmission of force through these hair structures.

In order to explore this concept, Chris Hill has created a whisker assembly for sensory augmentation, substituting flex sensors for the stiff hairs that we as humans don’t possess. The sensors—four are used here—vary resistance when bent, furnishing information about their status to the Arduino Uno that controls the wearable device. Forehead-mounted vibratory motors are pulsed via PWM outputs in response, allowing the user to feel what’s going on in the surrounding environment.

If this looks familiar, Hill is quick to credit Nicholas Gonyea’s Whisker Sensory Extension Wearable as the basis for this project. He hopes his take on things improves the original, making it lighter, more cost-effective, and easier to construct. 

The purpose of this project was to focus on the creation of novel, computationally-enriched “sensory extensions” that allow for augmented-sensing of the natural world. My major effort with this project was devoted to the fabrication and implementation of sensory augmentations that will extend a sense through sensors and respond with a tactile output for the user. The intent is to enable anyone to fabricate their own sensory extensions, and thusly map intrinsically human/animal senses onto hardware. Effectively extending our senses in new and exciting ways that will lead to a better understanding of how our brain is able to adapt to new external senses.

While you might have never considered the idea, looms—especially the punchcard-driven Jacquard loom, which helped inform both Ada Lovelace and Charles Babbage’s pioneering work—are an important part of computing history. As reported here, Victoria Manganiello and Julian Goldman have created an awe-inspiring ode to this computing heritage in the form of a handwoven tapestry that constantly changes the way it looks, aptly named “Computer 1.0.”

The tapestry, which was recently on display at the Museum of Arts and Design in New York City, stretches nine meters in length and features tubing woven throughout. An Arduino actuates pumps and valves to produce familiar patterns in this tubing with blue-dyed water and air.

These patterns soon become abstract and perhaps more open to interpretation, though with more development it’s noted that images and even smartphone-readable designs could be possible. 

Be sure to see the short demo of this incredible installation in the video below! 

A handwoven textile activated by computer code, Computer 1.0 explores connections between weaving and technology. For the project, Victoria Manganiello invited designer Julian Goldman to collaborate on designing and programming a pump controlled by Arduino microcomputers to move precise sequences of air and liquid through the approximately 2,000 feet of tubing woven through the cloth. The movement of the air and liquid evokes traditional weaving patterns such as bird’s eye, monk’s cloth, and twill. And the operating system—the computer and the pump—is not kept out of sight in the service of the woven screen and the pixelated patterns that run across it, but rather are an integral part of the work; nothing is hidden.

Manganiello’s textile reflects and expands on the ob­scured history of weaving and coding, calling attention to the “under-over, under-over” movement of thread becoming cloth that originally inspired the “zero-one-zero-one” of binary code. The jacquard loom of 1801, which used punch cards to program the movement of thread into increasingly complex woven patterns, is a direct, though frequently forgotten, ancestor of modern computers.

Even though machine learning AKA ‘deep learning’ / ‘artificial intelligence’ has been around for several decades now, it’s only recently that computing power has become fast enough to do anything useful with the science.

However, to fully understand how a neural network (NN) works, [Dimitris Tassopoulos] has stripped the concept down to pretty much the simplest example possible – a 3 input, 1 output network – and run inference on a number of MCUs, including the humble Arduino Uno. Miraculously, the Uno processed the network in an impressively fast prediction time of 114.4 μsec!

Whilst we did not test the code on an MCU, we just happened to have Jupyter Notebook installed so ran the same code on a Raspberry Pi directly from [Dimitris’s] bitbucket repo.

He explains in the project pages that now that the hype about AI has died down a bit that it’s the right time for engineers to get into the nitty-gritty of the theory and start using some of the ‘tools’ such as Keras, which have now matured into something fairly useful.

In part 2 of the project, we get to see the guts of a more complicated NN with 3-inputs, a hidden layer with 32 nodes and 1-output, which runs on an Uno at a much slower speed of 5600 μsec.

This exploration of ML in the embedded world is NOT ‘high level’ research stuff that tends to be inaccessible and hard to understand. We have covered Machine Learning On Tiny Platforms Like Raspberry Pi And Arduino before, but not with such an easy and thoroughly practical example.

When riding a motorcycle, it’s important to be seen, and if other vehicles can see your brake lights and turn signals as well, all the better. To help with visibility, YouTuber “MechTools” outfitted his helmet with a brake light and turn indicators that activate along with the motorcycle’s built-in signals.

The video below shows off how it was built, using an Arduino Uno onboard the motorcycle, plus a Nano embedded in the helmet. A pair of nRF24L01 transceivers enable the two Arduinos to communicate wirelessly, and three TIP122 transistors controls the lighting directly for sufficient power output.

While a neat concept, be sure that you don’t compromise your helmet’s structural integrity or legality if you try something similar! Code is available in the video’s description.