When you think of world-changing devices, you usually don’t think of the washing machine. However, making laundry manageable changed not only how we dress but how much time people spent getting their clothes clean. So complaining about how laborious our laundry is today would make someone from the 1800s laugh. Still, we all hate the laundry and [Andrew Dupont], in particular, hates having to check on the machine to see if it is done. So he made Laundry Spy.
How do you sense when the machine — either a washer or a dryer — is done? [Andrew] thought about sensing current but didn’t want to mess with house current. His machines don’t have LED indicators, so using a light sensor wasn’t going to work either. However, an accelerometer can detect vibrations in the machine and most washers and dryers vibrate plenty while they are running.
The four-part build log shows how he took an ESP8266 and made it sense when the washer and dryer were done so it could text his cell phone. He’d already done a similar project with an Adafruit HUZZAH. But he wanted to build in some new ideas and currently likes working with NodeMCU. While he was at it he upgraded the motion sensor to an LIS3DH which was cheaper than the original sensor.
[Andrew] already runs Node – RED on a Raspberry Pi, so incorporating this project with his system was a snap. Of course, you could adapt the approach to lots of other things, as well. The device produces MQTT messages and Node – RED subscribes to them. The Pushover handles the text messaging. Node – RED has a graphical workflow that makes integrating all the pieces very intuitive. Here’s the high-level workflow:
You might wonder why he didn’t just have the ESP8266 talk directly to Pushover. That is possible, of course, but in part 2, [Andrew] enumerates some good reasons for his design. He wants to decouple components in the system for easier future upgrades. And MQTT is simple to publish on the sensor side of things compared to API calls which are handled by the Raspberry Pi for now.
If you have about 10 hours to kill, you can use [Edje Electronics’s] instructions to install TensorFlow on a Raspberry Pi 3. In all fairness, the amount of time you’ll have to babysit is about an hour. The rest of the time is spent building things and you don’t need to watch it going. You can see a video on the steps required below.
You need the Pi with at least a 16 GB SD card and a USB drive with at least 1 GB of free space. This not only holds the software, but allows you to create a swap file so the Pi will have enough virtual memory to build everything required.
Fun fact, the Osborne 1 debuted with a price tag equivalent to about $5,000 in today’s value. With a gigantic 9″ screen and twin floppy drives (for making mix tapes, right?) the real miracle of the machine was its portability, something unheard of at the time. The retrocomputing trend is to lovingly and carefully restore these old machines to their former glory, regardless of how clunky or underpowered they are by modern standards. But sometimes they can’t be saved yet it’s still possible to gut and rebuild the machine with modern hardware, like with this Raspberry Pi used to revive an Osborne 1.
Purists will turn their nose up at this one, and we admit that this one feels a little like “restoring” radios from the 30s by chucking out the original chassis and throwing in a streaming player. But [koff1979] went to a lot of effort to keep the original Osborne look and feel in the final product. We imagine that with the original guts replaced by a Pi and a small LCD display taking the place of the 80 character by 24 line CRT, the machine is less strain on the shoulder when carrying it around. (We hear the original Osborne 1 was portable in the same way that an anvil is technically portable.) The Pi runs an emulator to get the original CP/M experience; it even runs Wordstar. The tricky part about this build was making the original keyboard talk to the Pi, which was accomplished with an Arduino that translates key presses to USB.
With Google’s near-monopoly on the internet, it can be difficult to get around in cyberspace without encountering at least some aspect of this monolithic, data-gathering giant. It usually takes a concerted effort, but it is technically possible to do. While [Mat] is still using some Google products, he has at least figured out a way to get Google Home to work with location data without actually sharing that data with Google, which is a step in the right direction.
[Mat]’s goal was to use Google’s location sharing features through Google Home, but without the creepiness factor of Google knowing everything about his life, and also without the hassle of having to use Google Maps. He’s using a few things to pull this off, including a NodeRED server running on a Raspberry Pi Zero, a free account from If This Then That (IFTTT), Tasker with AutoRemote plugin, and the Google Maps API key. With all of that put together, and some configuration of IFTTT he can ask his Google assistant (or Google Home) for location data, all without sharing that data with Google.
This project is a great implementation of Google’s tools and a powerful use of IFTTT. And, as a bonus, it gets around some of the creepiness factor that Google tends to incorporate in their quest to know all the data.
It was only a matter of time. Everything else is getting its data logged and reported to the Internet for detailed analysis, so why should our rodents be any different? The cover story is that [Nicole Horward] hooked her pet hamster Harold up to the web because she wanted to see if he was getting as much exercise as he should. The real reason is, of course, that Harold wanted to show off to his “friends” on Hamsterbook.
The hardware side of this hack is very simple, a magnetic door sensor (like the kind used in alarm systems) is used to detect each time the wheel makes a complete rotation. The sensor is hooked up to the GPIO pins of a Raspberry Pi, where it’s read by a Python script. A small LCD screen was added to give some visual feedback on Harold’s daily activity, and the whole thing was boxed up in a laser cut enclosure.
That gave [Nicole] a cute little display next to Harold’s cage, but it didn’t do much for analyzing his activity. For that, a script is used to upload the data every minute to a ThingSpeak channel via MQTT. This automatically generates attractive graphs from the raw data, making it much easier to visualize what’s happening over the long term.
If you’re building a CNC router, laser cutter, or even 3D printer, you’ll usually be looking at a dedicated controller. This board takes commands from a computer, often in the form of G-Code, and interprets that into movement commands to the connected stepper motors. Historically this has been something of a necessary evil, as there was really no way to directly control stepper motors with a computer fast enough to be useful. That may not be the case anymore.
Thanks to the Raspberry Pi (and similar boards), we now have Linux computers with plenty of GPIO pins. The only thing missing is the software to interpret the G-Code and command the steppers over GPIO, which thanks to [pantadeusz], we now have. Called raspigcd, this software interprets a subset of G-Code to provide real-time control over connected steppers fast enough to drive a small CNC router.
Of course, you can’t directly control a beefy stepper motor to the GPIO pins of a Pi. You’ll let out all the magic smoke. But you can wire it up directly to a stepper driver board. These little modules connect up to a dedicated power supply and handle the considerable current draw of the steppers, all you need to do is provide them the number of steps and direction of travel.
This method of direct control offers some very interesting possibilities for small, low-cost, CNC projects. Not only can you skip the control board, you could conceivably handle the machine’s user interface (either directly via a touch screen or over the network) on the same Pi.
We’ve seen attempts at creating all-in-one Linux stepper controllers in the past, but the fact that anyone with a Raspberry Pi 2 or 3 (the boards this software has currently been tested on) can get in on the action should really help spur along development. Has anyone used this?
The Proxxon MF70 is a nice desktop sized milling machine with a lot of useful add-on accessories available for it, making it very desirable for a hacker to have one in his or her home workshop. But its 20000 rpm spindle can cause quite the racket and invite red-faced neighbors. Also, how do you use a milling machine in your home-workshop without covering the whole area in metal chips and sawdust? To solve these issues, [Tim Lebacq] is working on Soundproofing his CNC mill conversion.
To meet his soundproof goal, he obviously had to first convert the manual MF70 to a CNC version. This is fairly straightforward and has been done on this, and similar machines, in many different ways over the years. [Tim] stuck with using the tried-and-tested controller solution consisting of a Raspberry Pi, an Arduino Uno and a grbl shield sandwich, with stepper motor drivers for the three NEMA17 motors. The electronics are housed inside the reclaimed metal box of an old power supply. Since the Proxxon MF70 is already designed to accept a CNC conversion package, mounting the motors and limit switches is pretty straightforward making it easy for [Tim] to make the upgrade.
Soundproofing the box is where he faced unknown territory. The box itself is made from wooden frames lined with particle board. A pair of drawer slides with bolt-action locks is used for the front door which opens vertically up. He’s also thrown in some RGB strips controlled via the Raspberry-Pi for ambient lighting and status indications. But making it soundproof had him experimenting with various materials and techniques. Eventually, he settled on a lining of foam sheets topped up with a layer of — “bubble wrap” ! It seems the uneven surface of the bubble wrap is quite effective in reducing sound – at least to his ears. Time, and neighbours, will tell.
Maybe high density “acoustic foam” sheets would be more effective (the ones similar to “egg crate” style foam sheets, only more dense)? Cleaning the inside of the box could be a big challenge when using such acoustic foam, though. What would be your choice of material for building such a sound proof box? Let us know in the comments below. Going back many years, we’ve posted about this “Portable CNC Mill” and a “Mill to CNC Conversion” for the Proxxon MF70. Seems like a popular machine among hackers.
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