How to Eclipse When All You Have is a Welding Helmet

What do you do if you don’t trust cheap eclipse-watching glasses from the internet? What about if everyone’s sold out? Well, if you want to watch the eclipse and you have an auto-darkening welding helmet, you can do what [daniel_reetz] did and hack something together with a remote and your welding helmet to let you see the eclipse without blinding yourself.

Essentially, the hack tricks the helmet’s sensors into thinking it’s very bright. [Daniel_reetz] accomplishes this by gluing a remote with an infrared LED to the side of the helmet and covering it with a 50mm plastic lid. There are two sensors on [daniel_reetz]’s helmet, so he covers the other one with aluminum tape. What this means is that when he presses a button on the remote, the lid-covered sensor thinks it’s very bright out and since the other sensor is covered, it darkens the lens of the mask.

I’m sure some of our readers could come up with a more sophisticated method that would allow you to do something other with your hand than press the remote buttons, but this is a quick and easy hack that’ll get you able to take a quick look at the eclipse – assuming you have a welding mask capable of shading to level 13 or 14. If you are hoping to catch a glimpse of the eclipse, check out the safety guide from NASA just to make sure your eyes are safe. For another method of viewing the eclipse, check out this wearable pinhole camera. For another welding mask hack, check out this augmented reality mask.

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Use a Drill to Power Your Flipbooks

[WolfCat] of Wolfcatworkshop is creating a hand-animated split-flap animation. But what do you use to test your animation once it’s on the split-flaps? Well, to test it out, [WolfCat] used a drill to give it motion. DoodlersAnonymous has some pics and an interview with [WolfCat] about his animation and there are some pictures on his Instagram page.

Technically, what [WolfCat] wanted to make is a “mutoscope,” a hand-cranked precursor to the movie projector that had its heyday in the late 19th and early 20th century. Originally installed in penny arcades and the like, mutoscopes were single-viewer apparatus. The viewer cranks the handle and the animated cards inside rotate around, stopped briefly by a bit of metal at the top in order to show a frame. The basic idea is similar to the way split-flap clocks or signs work.

[WolfCat] hand drew the animation for his movie and then scanned and printed out each frame. The frames were then transferred to a pair of flaps. [WolfCat] wanted to see how it would look when animated, but didn’t have any plans at the time for a case or a hand crank, so he found the closest tool that would do the job – a cordless drill. Attaching the drill and using a bit of card or wood as a stopper, [WolfCat] could see how the end result would look and could then start work on the case and crank.

The drill is a quick and easy way to see what the finished product would look like. Once he’s got it working, [WolfCat] could check out this 3D printed mutoscope case, or this flip dot animated display.

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We Should Stop Here, It’s Bat Country!

[Roland Meertens] has a bat detector, or rather, he has a device that can record ultrasound – the type of sound that bats use to echolocate. What he wants is a bat detector. When he discovered bats living behind his house, he set to work creating a program that would use his recorder to detect when bats were around.

[Roland]’s workflow consists of breaking up a recording from his backyard into one second clips, loading them in to a Python program and running some machine learning code to determine whether the clip is a recording of a bat or not and using this to determine the number of bats flying around. He uses several Python libraries to do this including Tensorflow and LibROSA.

The Python code breaks each one second clip into twenty-two parts. For each part, he determines the max, min, mean, standard deviation, and max-min of the sample – if multiple parts of the signal have certain features (such as a high standard deviation), then the software has detected a bat call. Armed with this, [Roland] turned his head to the machine learning so that he could offload the work of detecting the bats. Again, he turned to Python and the Keras library.

With a 95% success rate, [Roland] now has a bat detector! One that works pretty well, too. For more on detecting bats and machine learning, check out the bat detector in this list of ultrasonic projects and check out this IDE for working with Tensorflow and machine learning.

DIY VT220 Keyboard

There’s always been interest in the computers of old, and people love collecting and restoring them. When [peterbjornx] got his hands on a DEC VT220 video terminal, it was in good shape – it needed a bit of cleaning, but it also needed a keyboard. [Peter] couldn’t afford to buy the keyboard, but the service manual for it was available, so he decided to convert a modern keyboard to work with his new terminal.

The original keyboard for the VT220 is the LK201. This keyboard communicates with the terminal using 8-N-1 (eight data bits, no parity, one stop bit) over RS232 at 4800 baud. This meant that it would be pretty simple to implement this on microcontroller in order to communicate with the terminal. [Peter] chose the Arduino Nano. However, the LK200 was more than just a keyboard for communicating with the terminal, it also housed a speaker and LEDs which the terminal used to communicate with the user. Rather than put these into the adapter unit, [Peter] decided to put these into the keyboard – a few holes and a bit of wiring, and they were in.

[Peter]’s write-up includes a description of some of the issues he encountered as well as a picture of the keyboard. He’s put the schematic online and the code up on GitHub. In case you were wondering, he used Vim on the VT220 to write his article. You could also use a Raspberry Pi to help out your dumb terminal, or just hook the terminal directly to your Linux box and go from there.

Raspberry Pi Tracks Office Happiness

It’s always great to see people who haven’t had the opportunity to work with hardware like the Raspberry Pi before come up with a great project and have fun putting it together.  [Katja]’s company has a two-day hackfest where employees can work on some cool non-work-related projects. [Katja]’s team decided to use a Raspberry Pi and some buttons and LEDs to create a ‘happiness tracker‘ for the company.

The resulting project is mounted near the entrance to the office and when they come in or leave, an employee can push one of four buttons to indicate their mood at the time, ‘bad,’ ‘not so good,’ ‘good’ or ‘super.’ The result is tracked and an overall impression of the office’s happiness is the result.

The project consists of the aforementioned Raspberry Pi, four push buttons, five LEDs that animate when a button is pressed and another LED that shows the system is currently up and working. When a user presses a button, the five LEDs animate in the shape of a check mark to show that the button press was successful. A Python script running at startup on the Pi takes care of detecting button pressing, lighting LEDs and sending a message to the server which monitors the level of happiness.

It’s a simple project, but that’s exactly what you need when you start with hardware you haven’t worked with before. It seems like [Katja]’s team had fun building the project and they hope that this can help gauge the overall wellbeing of the office. [Katja]’s blog post has an embedded video of the project in action. In the meantime, check out this bit of facial recognition software that determines how happy you are based on your smile, or this project that lets you know how happy your plant is.

Designing the Atom Smasher Guitar Pedal

[Alex Lynham] has been creating digital guitar pedals for a while and after releasing the Atom Smasher, a glitchy lo-fi digital delay pedal, he had people start asking him how he designed digital effects pedals rather than analog effects. In fact, he had enough interest, that he wrote an article on it.

The article starts with some background on [Alex], the pedals he’s built and why he chose not to work on pedals full-time. Eventually, the article gets to the how [Alex] designed the Atom Smasher. He starts by describing the chip he used, the same one that many hobbyists, as well as commercial builders, use for delay based effects – the SpinSemi FV-1.

The FV-1 is a SMD chip used for digital delays and other effects that require a delay line – reverbs, choruses, flangers, etc. It’s programmed with an assembly-style language called SpinASM. [Alex] goes over some of the tools and references he used when designing for the pedal. He also has a list of tips for would-be effect pedal designers which work whether you’re designing digital or analogue effects.

[Alex] ends his article saying that, in the future, he might make the schematic and code available, but for the moment he’s not. The FV-1 is an interesting chip, and [Alex]’s article gives a nice high-level look at its features and how to develop for it. For some interesting guitar pedal related articles, check out this one using effects pedals to get better audio in your car, and here’s one about playing with DSP and designing a pedal with it.

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Monitor Your City’s Air Quality

[Radu Motisan]’s entry in the 2017 Hackaday Prize is a series of IoT Air Quality monitors, the City Air Quality project. According to [Radu], air pollution is the single largest environmental cause of premature death in urban Europe and transport is the main source. [Radu] has created a unit that can be deployed throughout a city and has sensors on it to report on the air quality.

The hardware has a laser light scattering sensor for particulate matter and 4 electromechanical sensors for carbon monoxide, nitrogen dioxide, sulfur dioxide and ozone (these sense the six parameters that are recognized as having significant health impact by multiple countries.) These sensors have2-yearear lifespan, so they are installed in sockets for easy replacement, and if needed, you can swap to different sensors to detect different things. The PCBs for the hardware are separated into a WiFi version and a LoRaWAN version and the software runs on an ATMega328 – the PCB has the standard six-pin ISP connection for programming.

The data collected is sent to a server where it is adjusted based on the unit’s calibration parameters and stored in a database per sensor. This makes servicing the sensors at the end of their life easier as all that’s required is replacing the sensors in the unit and changing the calibration parameters stored for that unit, the software changes are required. The server offers the data via a RESTful API so that building dashboards with the stats and charts become easy.

[Radu] used an off the shelf module as the first prototype and attached it to a car while driving around. He used this to test out the plan and work on the server. He then proceeded to designing the PCB hardware and the enclosure for the final unit. This work is an extension of [Radu]’s previous work, spotlit here in the 2015 Hackaday Prize, but also check out this project to put air quality sensors in the classroom.

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