Multi-channel Analog Input Module Is A Good Jumping-off Point For Many Projects

[Scott Harden] has already produced some projects which measure analog inputs. But he’s got plans for more and wanted a base system for graphing analog signals. You can see the small board next to his laptop which offers the ability to sample up to six signals and push them to a PC via USB.

The ATmega48 and a few supporting components are all you’ll find on that board. The USB connection is taken care of by an FTDI cable. He went that route because the cables are relatively cheap, easy to come by, and already have driver support on all the major operating systems. If you look at the screen you can see a window graphing one analog input in real-time. He wrote this in Python (which is once again a cross-platform tool) and it has no problem graphing all six inputs at once.

This is immediately useful as an upgrade to [Scott’s] ECG machine. His future plans include a Pulse Oximeter, EEG, and EEG.

Using The GPIO Pins On A Raspberry Pi

In addition to being a serviceable single board computer, the Raspberry Pi also has a header full of GPIO pins at your beck and call. [Tedbot] sent in a great tutorial on using these pins with Python, Bash, and C.

The GPIO pins on the Raspi are arranged in a 2×13 header. Until Sparkfun manages to manufacture a decent Raspi protoboard, the easiest way to break these pins out is with an old IDE ribbon cable. After plugging the other end into a breadboard, [Tedbot] had an easily accessible set of Raspi pins.

To control these pins, [Tedbot] found two libraries: the first is WiringPi that implements a C-style, Arduino-like programming environment on the Raspi. The second is the RPi.GPIO Python package. Since the Raspi runs Linux, and everything in Unix is a file, [Tedbot] used a shell script to blink a LED.

One word of warning if you’re building a board to extend the capabilities of the Raspi: these pins aren’t 5 V tolerant, so you’ll need to throw in a buffer or level converter when building a Raspi circuit.

Edit: Adafruit is releasing a Pi Plate prototyping board in a few weeks. Neat, huh?

MyHDL Python Programming Option For FPGA

MyHDL is a Python module that brings FPGA programming into the Python environment. [Christopher Felton] tipped us off about a simple tutorial he just finished that gives an overview of how the module is used.

You may remember hearing about PyCPU a couple days ago which can run very simple Python code on a FPGA. There was a healthy discussion in the comments section comparing PyCPU and MyHDL. Although they may seem similar at first, the two are quite different. PyCPU creates a processor on the FPGA chip which can execute a small range of Python code. MyHDL actually implements Hardware Description Language in the Python environment. Once you’re used HDL to model your hardware choices in a Python script, it is converted to VHDL then fed to the toolchain and pushed to the chip like normal.

This is not an absolute beginner’s experience. But if you’re well-versed in Python it makes the jump to HDL a lot easier because you’ll be working with syntax that is already familiar to you.

Scraping Blogs For Fun And Profit

Sometimes when you’re working on a problem, a solution is thrown right at your face. We found ourselves in this exact situation a few days ago while putting together Hackaday’s new retro edition; a way to select a random Hackaday article was needed and [Alexander van Teijlingen] of codepanel.net just handed us the solution.

To grab every Hackaday URL ever, [Alex] wrote a small Python script using the Beautiful Soup screen scraping library. The program starts on Hackaday’s main page and grabs every link to a Hackaday post before going to the next page. It’s not a terribly complex build, but we’re gobsmacked a solution to a problem we’re working on would magically show up in our inbox.

Thanks to [Alex], writing a cron job to automatically update our new retro edition just got a whole lot easier. If you’d like to check out a list of every Hackaday post ever (or at least through two days ago), you can grab 10,693 line text file here.

Programming FPGAs With Python

If you’ve ever wanted to jump into the world of FPGAs but don’t want to learn yet another language, you can now program an FPGA with Python. PyCPU converts very, very simple Python code into either VHDL or Verilog. From this, a hardware description can be uploaded to an FPGA.

The portion of the Python language supported by PyCPU is extremely minimal, with only ints being the only built-in data type supported. Of course ifs and whiles are still included along with all the assignments and operators. A new addition is a way to get digital IO access with Python, and obvious requirement if you’re going to be programming Silicon.

PyCPU surely won’t replace VHDL or Verilog anytime soon, but if you’re looking to get into FPGAs and the ‘telling a chip what to be’ paradigm it offers, it’s certainly a tool worth looking into.

Hats off to [hardsoftlucid] for sending this in. Our wonderful (we mean that, really) noticed a few mistakes when this was first posted. Those mistakes have been corrected.

Simplest Of SL4A Microbridge Examples

We’re familiar with the daunting task of sifting through mountains of code in hopes you can learn how something works. So when a simple example like this SL4A LED toggle comes along we’re thankful for the trimmed fat. If you’re looking to use an Android device to control your Arduino hardware this will be huge shove in the right direction.

The microbridge is used to get the Arduino talking with the Android phone. It involves a USB host shield that lets you connect the two devices via a USB cable. With the USB debugging enabled on the phone, you can use Scripting Layer for Android as a user interface. In this case, a set of Python scripts builds the button and readout seen on the screen above. They also handle sending and receiving commands based on user input. This means you don’t really need to know anything about Android development. We think it would be a great way to get your project through the development stages, and you could learn to write a traditional App later on.

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Catch Neighborhood Speeders With Your Webcam

[John] is keeping the neighborhood safe by keeping an eye out for speeders. Well, he’s really keeping a webcam out for speeders. His technique doesn’t use radar or lasers. He’s processing webcam frames in Python to calculate speed.

It comes down to some basic image manipulation. He firsts gathers the images necessary to make the calculations by using a motion-detecting webcam program called YawCam. The images are analyzed to establish which parts have changed between frames; this gets rid of all the stationary objects. Now the frames can be compared to establish the distance in pixels. By calibrating the shot through measurements of the target area, this data can be directly converted into actual distance. It is then compared with the timestamps from each frame to arrive at speed. This can be used for vehicles on the street like we see above, or more whimsical measurements like pet turtle progress.