Latest Raspberry Pi OS update – May 2020

Along with yesterday’s launch of the new 8GB Raspberry Pi 4, we launched a beta 64-bit ARM version of Debian with the Raspberry Pi Desktop, so you could use all those extra gigabytes. We also updated the 32-bit version of Raspberry Pi OS (the new name for Raspbian), so here’s a quick run-through of what has changed.

NEW Raspberry Pi OS update (May 2020)

An update to the Raspberry Pi Desktop for all our operating system images is also out today, and we’ll have more on that in tomorrow’s blog post. For now, fi…

Bookshelf

As many of you know, we have our own publishing company, Raspberry Pi Press, who publish a variety of magazines each month, including The MagPi, HackSpace magazine, and Wireframe. They also publish a wide range of other books and magazines, which are released either to purchase as a physical product (from their website) or as free PDF downloads.

To make all this content more visible and easy to access, we’ve added a new Bookshelf application – you’ll find it in the Help section of the main menu.

Bookshelf shows the entire current catalogue of free magazines – The MagPi, HackSpace magazine and Wireframe, all with a complete set of back issues – and also all the free books from Raspberry Pi Press. When you run the application, it automatically updates the catalogue and shows any new titles which have been released since you last ran it with a little “new” flash in the corner of the cover.

To read any title, just double-click on it – if it is already on your Raspberry Pi, it will open in Chromium (which, it turns out, is quite a good PDF viewer); if it isn’t, it will download and then open automatically when the download completes. You can see at a glance which titles are downloaded and which are not by the “cloud” icon on the cover of any file which has not been downloaded.

All the PDF files you download are saved in the “Bookshelf” directory in your home directory, so you can also access the files directly from there.

There’s a lot of excellent content produced by Raspberry Pi Press – we hope this makes it easier to find and read.

Magnifier

As mentioned in my last blog post (here), one of the areas we are currently trying to improve is accessibility to the Desktop for people with visual impairments. We’ve already added the Orca screen reader (which has had a few bug fixes since the last release which should make it work more reliably in this image), and the second recommendation we had from AbilityNet was to add a screen magnifier.

This proved to be harder than it should have been! I tried a lot of the existing screen magnifier programs that were available for Debian desktops, but none of them really worked that well; I couldn’t find one that worked the way the magnifiers in the likes of MacOS and Ubuntu did, so I ended up writing one (almost) from scratch.

To install it, launch Recommended Applications in the new image and select Magnifier under Universal Access. Once it has installed, reboot.

You’ll see a magnifying glass icon at the right-hand end of the taskbar – to enable the magnifier, click this icon, or use the keyboard shortcut Ctrl-Alt-M. (To turn the magnifier off, just click the icon again or use the same keyboard shortcut.)

Right-clicking the magnifier icon brings up the magnifier options. You can choose a circular or rectangular window of whatever size you want, and choose by how much you want to zoom the image. The magnifier window can either follow the mouse pointer, or be a static window on the screen. (To move the static window, just drag it with the mouse.)

Also, in some applications, you can have the magnifier automatically follow the text cursor, or the button focus. Unfortunately, this depends on the application supporting the required accessibility toolkit, which not all applications do, but it works reasonably well in most included applications. One notable exception is Chromium, which is adding accessibility toolkit support in a future release; for now, if you want a web browser which supports the accessibility features, we recommend Firefox, which can be installed by entering the following into a terminal window:

sudo apt install firefox-esr

(Please note that we do not recommend using Firefox on Raspberry Pi OS unless you need accessibility features, as, unlike Chromium, it is not able to use the Raspberry Pi’s hardware to accelerate video playback.)

I don’t have a visual impairment, but I find the magnifier pretty useful in general for looking at the finer details of icons and the like, so I recommend installing it and having a go yourself.

User research

We already know a lot of the things that people are using Raspberry Pi for, but we’ve recently been wondering if we’re missing anything… So we’re now including a short optional questionnaire to ask you, the users, for feedback on what you are doing with your Raspberry Pi in order to make sure we are providing the right support for what people are actually doing.

This questionnaire will automatically be shown the first time you launch the Chromium browser on a new image. There are only four questions, so it won’t take long to complete, and the results are sent to a Google Form which collates the results.

You’ll notice at the bottom of the questionnaire there is a field which is automatically filled in with a long string of letters and numbers. This is a serial number which is generated from the hardware in your particular Raspberry Pi which means we can filter out multiple responses from the same device (if you install a new image at some point in future, for example). It does not allow us to identify anything about you or your Raspberry Pi, but if you are concerned, you can delete the string before submitting the form.

As above, this questionnaire is entirely optional – if you don’t want to fill it in, just close Chromium and re-open it and you won’t see it again – but it would be very helpful for future product development if we can get this information, so we’d really appreciate it if as many people as possible would fill it in.

Other changes

There is also the usual set of bug fixes and small tweaks included in the image, full details of which can be found in the release notes on the download page.

One particular change which it is worth pointing out is that we have made a small change to audio. Raspberry Pi OS uses what is known as ALSA (Advanced Linux Sound Architecture) to control audio devices. Up until now, both the internal audio outputs on Raspberry Pi – the HDMI socket and the headphone jack – have been treated as a single ALSA device, with a Raspberry Pi-specific command used to choose which is active. Going forward, we are treating each output as a separate ALSA device; this makes managing audio from the two HDMI sockets on Raspberry Pi 4 easier and should be more compatible with third-party software. What this means is that after installing the updated image, you may need to use the audio output selector (right-click the volume icon on the taskbar) to re-select your audio output. (There is a known issue with Sonic Pi, which will only use the HDMI output however the selector is set – we’re looking at getting this fixed in a future release.)

Some people have asked how they can switch the audio output from the command line without using the desktop. To do this, you will need to create a file called .asoundrc in your home directory; ALSA looks for this file to determine which audio device it should use by default. If the file does not exist, ALSA uses “card 0” – which is HDMI – as the output device. If you want to set the headphone jack as the default output, create the .asoundrc file with the following contents:

defaults.pcm.card 1
defaults.ctl.card 1

This tells ALSA that “card 1” – the headphone jack – is the default device. To switch back to the HDMI output, either change the ‘1’s in the file to ‘0’s, or just delete the file.

How do I get it?

The new image is available for download from the usual place: our Downloads page.

To update an existing image, use the usual terminal command:

sudo apt update
sudo apt full-upgrade

To just install the bookshelf app:

sudo apt update
sudo apt install rp-bookshelf

To just install the magnifier, either find it under Universal Access in Recommended Software, or:

sudo apt update
sudo apt install mage

You’ll need to add the magnifier plugin to the taskbar after installing the program itself. Once you’ve installed the program and rebooted, right-click the taskbar and choose Add/Remove Panel Items; click Add, and select the Magnifier option.

We hope you like the changes — as ever, all feedback is welcome, so please leave a comment below!

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8GB Raspberry Pi 4 on sale now at $75

The long-rumoured 8GB Raspberry Pi 4 is now available, priced at just $75.

Raspberry Pi 4 is almost a year old, and it’s been a busy year. We’ve sold nearly 3 million units, shipped a couple of minor board revisions, and reduced the price of the 2GB variant from $45 to $35. On the software side, we’ve done enormous amounts of work to reduce the idle and loaded power consumption of the device, passed OpenGL ES 3.1 conformance, started work on a Vulkan driver, and shipped PXE network boot mode and a prototype of USB mass storage boot mode – all this alongside the usual round of bug fixes, feature additions, and kernel version bumps.

While we launched with 1GB, 2GB and 4GB variants, even at that point we had our eye on the possibility of an 8GB Raspberry Pi 4. We were so enthusiastic about the idea that the non-existent product made its way into both the Beginner’s Guide and the compliance leaflet.

Oops.

The BCM2711 chip that we use on Raspberry Pi 4 can address up to 16GB of LPDDR4 SDRAM, so the real barrier to our offering a larger-memory variant was the lack of an 8GB LPDDR4 package. These didn’t exist (at least in a form that we could address) in 2019, but happily our partners at Micron stepped up earlier this year with a suitable part. And so, today, we’re delighted to announce the immediate availability of the 8GB Raspberry Pi 4, priced at just $75.

Multum in parvo

It’s worth reflecting for a moment on what a vast quantity of memory 8GB really is. To put it in retro-perspective (retrospective?), this is a BBC Micro‘s worth of memory for every bit in the memory of the BBC Micro; it’s a little over 13,000 times the 640KB that Bill Gates supposedly thought should be enough for anyone (sadly, it looks as though this quote is apocryphal).

If you’re a power user, intending to compile and link large pieces of software or run heavy server workloads, or you simply want to be able to have even more browser tabs open at once, this is definitely the Raspberry Pi for you.

What else has changed?

To supply the slightly higher peak currents required by the new memory package, James has shuffled the power supply components on the board, removing a switch-mode power supply from the right-hand side of the board next to the USB 2.0 sockets and adding a new switcher next to the USB-C power connnector. While this was a necessary change, it ended up costing us a three-month slip, as COVID-19 disrupted the supply of inductors from the Far East.

New switcher, new inductors, new schedule

Other than that, this is the same Raspberry Pi 4 you’ve come to know and love.

What about 64-bit?

Our default operating system image uses a 32-bit LPAE kernel and a 32-bit userland. This allows multiple processes to share all 8GB of memory, subject to the restriction that no single process can use more than 3GB. For most users this isn’t a serious restriction, particularly since every tab in Chromium gets its own process. Sticking with a 32-bit userland has the benefit that the same image will run on every board from a 2011-era alpha board to today’s shiny new 8GB product.

But power users, who want to be able to map all 8GB into the address space of a single process, need a 64-bit userland. There are plenty of options already out there, including Ubuntu and Gentoo.

Not to be left out, today we’ve released an early beta of our own 64-bit operating system image. This contains the same set of applications and the same desktop environment that you’ll find in our regular 32-bit image, but built against the Debian arm64 port.

Both our 32-bit and 64-bit operating system images have a new name: Raspberry Pi OS. As our community grows, we want to make sure it’s as easy as possible for new users to find our recommended operating system for Raspberry Pi. We think the new name will help more people feel confident in using our computers and our software. An update to the Raspberry Pi Desktop for all our operating system images is also out today, and we’ll have more on that in tomorrow’s blog post.

You can find a link to the new 64-bit image, and some important caveats, in this forum post.

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Learning AI at school — a peek into the black box

“In the near future, perhaps sooner than we think, virtually everyone will need a basic understanding of the technologies that underpin machine learning and artificial intelligence.” — from the 2018 Informatics Europe & EUACM report about machine learning

As the quote above highlights, AI and machine learning (ML) are increasingly affecting society and will continue to change the landscape of work and leisure — with a huge impact on young people in the early stages of their education.

But how are we preparing our young people for this future? What skills do they need, and how do we teach them these skills? This was the topic of last week’s online research seminar at the Raspberry Pi Foundation, with our guest speaker Juan David Rodríguez Garcia. Juan’s doctoral studies around AI in school complement his work at the Ministry of Education and Vocational Training in Spain.

Juan David Rodríguez Garcia

Juan’s LearningML tool for young people

Juan started his presentation by sharing numerous current examples of AI and machine learning, which young people can easily relate to and be excited to engage with, and which will bring up ethical questions that we need to be discussing with them.

Of course, it’s not enough for learners to be aware of AI applications. While machine learning is a complex field of study, we need to consider what aspects of it we can make accessible to young people to enable them to learn about the concepts, practices, and skills underlying it. During his talk Juan demonstrated a tool called LearningML, which he has developed as a practical introduction to AI for young people.

Screenshot of a demo of Juan David Rodríguez Garcia's LearningML tool

Juan demonstrates image recognition with his LearningML tool

LearningML takes inspiration from some of the other in-development tools around machine learning for children, such as Machine Learning for Kids, and it is available in one integrated platform. Juan gave an enticing demo of the tool, showing how to use visual image data (lots of pictures of Juan with hats, glasses on, etc.) to train and test a model. He then demonstrated how to use Scratch programming to also test the model and apply it to new data. The seminar audience was very positive about the LearningML, and of course we’d like it translated into English!

Juan’s talk generated many questions from the audience, from technical questions to the key question of the way we use the tool to introduce children to bias in AI. Seminar participants also highlighted opportunities to bring machine learning to other school subjects such as science.

AI in schools — what and how to teach

Machine learning demonstrates that computers can learn from data. This is just one of the five big ideas in AI that the AI4K12 group has identified for teaching AI in school in order to frame this broad domain:

  1. Perception: Computers perceive the world using sensors
  2. Representation & reasoning: Agents maintain models/representations of the world and use them for reasoning
  3. Learning: Computers can learn from data
  4. Natural interaction: Making agents interact comfortably with humans is a substantial challenge for AI developers
  5. Societal impact: AI applications can impact society in both positive and negative ways

One general concern I have is that in our teaching of computing in school (if we touch on AI at all), we may only focus on the fifth of the ‘big AI ideas’: the implications of AI for society. Being able to understand the ethical, economic, and societal implications of AI as this technology advances is indeed crucial. However, the principles and skills underpinning AI are also important, and how we introduce these at an age-appropriate level remains a significant question.

Illustration of AI, Image by Seanbatty from Pixabay

There are some great resources for developing a general understanding of AI principles, including unplugged activities from Computer Science For Fun. Yet there’s a large gap between understanding what AI is and has the potential to do, and actually developing the highly mathematical skills to program models. It’s not an easy issue to solve, but Juan’s tool goes a little way towards this. At the Raspberry Pi Foundation, we’re also developing resources to bridge this educational gap, including new online projects building on our existing machine learning projects, and an online course. Watch this space!

AI in the school curriculum and workforce

All in all, we seem to be a long way off introducing AI into the school curriculum. Looking around the world, in the USA, Hong Kong, and Australia there have been moves to introduce AI into K-12 education through pilot initiatives, and hopefully more will follow. In England, with a computing curriculum that was written in 2013, there is no requirement to teach any AI or machine learning, or even to focus much on data.

Let’s hope England doesn’t get left too far behind, as there is a massive AI skills shortage, with millions of workers needing to be retrained in the next few years. Moreover, a recent House of Lords report outlines that introducing all young people to this area of computing also has the potential to improve diversity in the workforce — something we should all be striving towards.

We look forward to hearing more from Juan and his colleagues as this important work continues.

Next up in our seminar series

If you missed the seminar, you can find Juan’s presentation slides and a recording of his talk on our seminars page.

In our next seminar on Tuesday 2 June at 17:00–18:00 BST / 12:00–13:00 EDT / 9:00–10:00 PDT / 18:00–19:00 CEST, we’ll welcome Dame Celia Hoyles, Professor of Mathematics Education at University College London. Celia will be sharing insights from her research into programming and mathematics. To join the seminar, simply sign up with your name and email address and we’ll email the link and instructions. If you attended Juan’s seminar, the link remains the same.

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Meet your new robotic best friend: the MiRo-E dog

When you’re learning a new language, it’s easier the younger you are. But how can we show very young students that learning to speak code is fun? Consequential Robotics has an answer…

The MiRo-E is an ’emotionally engaging’ robot platform that was created on a custom PCB  and has since moved onto Raspberry Pi. The creators made the change because they saw that schools were more familiar with Raspberry Pi and realised the potential in being able to upgrade the robotic learning tools with new Raspberry Pi boards.

The MiRo-E was born from a collaboration between Sheffield Robotics, London-based SCA design studio, and Bristol Robotics Lab. The cute robo-doggo has been shipping with Raspberry Pi 3B+ (they work well with the Raspberry Pi 4 too) for over a year now.

While the robot started as a developers’ tool (MiRo-B), the creators completely re-engineered MiRo’s mechatronics and software to turn it into an educational tool purely for the classroom environment.

Three school children in uniforms stroke the robot dog's chin

MiRo-E with students at a School in North London, UK

MiRo-E can see, hear, and interact with its environment, providing endless programming possibilities. It responds to human interaction, making it a fun, engaging way for students to learn coding skills. If you stroke it, it purrs, lights up, move its ears, and wags its tail. Making a sound or clapping makes MiRo move towards you, or away if it is alarmed. And it especially likes movement, following you around like a real, loyal canine friend. These functionalities are just the basic starting point, however: students can make MiRo do much more once they start tinkering with their programmable pet.

These opportunities are provided on MiRoCode, a user-friendly web-based coding interface, where students can run through lesson plans and experiment with new ideas. They can test code on a virtual MiRo-E to create new skills that can be applied to a real-life MiRo-E.

What’s inside?

Here are the full technical specs. But basically, MiRo-E comprises a Raspberry Pi 3B+ as its core, light sensors, cliff sensors, an HD camera, and a variety of connectivity options.

How does it interact?

MiRo reacts to sound, touch, and movement in a variety of ways. 28 capacitive touch sensors tell it when it is being petted or stroked. Six independent RGB LEDs allow it to show emotion, along with DOF to move its eyes, tail, and ears. Its ears also house four 16-bit microphones and a loudspeaker. And two differential drive wheels with opto-sensors help MiRo move around.

What else can it do?

The ‘E’ bit of MiRo-E means it’s emotionally engaging, and the intelligent pet’s potential in healthcare have already been explored. Interaction with animals has been proved to be positive for patients of all ages, but sometimes it’s not possible for ‘real’ animals to comfort people. MiRo-E can fill the gap for young children who would benefit from animal comfort, but where healthcare or animal welfare risks are barriers.

The same researchers who created this emotionally engaging robo-dog for young people are also working with project partners in Japan to develop ‘telepresence robots’ for older patients to interact with their families over video calls.

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The Raspberry Pi Press store is looking mighty fine

Eagle-eyed Raspberry Pi Press fans might have noticed some changes over the past few months to the look and feel of our website. Today we’re pleased to unveil a new look for the Raspberry Pi Press website and its online store.

Did you know?

Raspberry Pi Press is the publishing imprint of Raspberry Pi (Trading) Ltd, which is part of the Raspberry Pi Foundation, a UK-based charity that does loads of cool stuff with computers and computer education.

Did you also know?

Raspberry Pi Press publishes five monthly magazines: The MagPi, HackSpace Magazine, Wireframe, Custom PC, and Digital SLR Photography. It also produces a plethora of project books and gorgeous hardback beauties, such as retro gamers’ delight Code the Classics, as well as Hello World, the computing and digital making magazine for educators! Phew!

And did you also, also know?

The Raspberry Pi Press online store ships around the globe, with copies of our publications making their way to nearly every single continent on planet earth. Antarctica, we’re looking at you, kid.

It’s upgrade time!

With all this exciting work going on, it seemed only fair that Raspberry Pi Press should get itself a brand new look. We hope you’ll enjoy skimming the sparkling shelves of our online newsagents and bookshop.

Ain’t nothin’ wrong with a little tsundoku

You can pick up all the latest issues of your favourite magazines or treat yourself to a book or three, and you can also subscribe to all our publications with ease. We’ve even added a few new payment options to boot.

New delivery options

We’ve made a few changes to our shipping options, with additional choices for some regions to make sure that you can easily track your purchases and receive timely and reliable deliveries, even if you’re a long way from the Raspberry Pi Press printshop.

Customers in the UK, the EU, North America, Australia, and New Zealand won’t see any changes to delivery options. We continue to work to make sure we’re offering the best price and service we can for everyone, no matter where you are.

Have a look and see what you think!

So hop on over to the new and improved Raspberry Pi Press website to see the changes for yourself. And if you have any feedback, feel free to drop Oli and the team an email at rpipresshelp@raspberrypi.com.

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Design your own Internet of Things with HackSpace magazine

In issue 31 of HackSpace magazine, out today, PJ Evans looks at DIY smart homes and homemade Internet of Things devices.

In the last decade, various companies have come up with ‘smart’ versions of almost everything. Microcontrollers have been unceremoniously crowbarred into devices that had absolutely no need for microcontrollers, and often tied to phone apps or web services that are hard to use and don’t work well with other products.

Put bluntly, the commercial world has struggled to deliver an ecosystem of useful smart products. However, the basic principle behind the connected world is good – by connecting together sensors, we can understand our local environment and control it to make our lives better. That could be as simple as making sure the plants are correctly watered, or something far more complex.

The simple fact is that we each lead different lives, and we each want different things out of our smart homes. This is why companies have struggled to create a useful smart home system, but it’s also why we, as makers, are perfectly placed to build our own. Let’s dive in and take a look at one way of doing this – using the TICK Stack – but there are many more, and we’ll explore a few alternatives later on.

Many of our projects create data, sometimes a lot of it. This could be temperature, humidity, light, position, speed, or anything else that we can measure electronically. To be useful, that data needs to be turned into information. A list of numbers doesn’t tell you a lot without careful study, but a line graph based on those numbers can show important information in an instant. Often makers will happily write scripts to produce charts and other types of infographics, but now open-source software allows anyone to log data to a database, generate dashboards of graphs, and even trigger alerts and scripts based on the incoming data. There are several solutions out there, so we’re going to focus on just one: a suite of products from InfluxData collectively known as the TICK Stack.

InfluxDB

The ‘I’ in TICK is the database that stores your precious data. InfluxDB is a time series database. It differs from regular SQL databases as it always indexes based on the time stamp of the incoming data. You can use a regular SQL database if you wish (and we’ll show you how later), but what makes InfluxDB compelling for logging data is not only its simplicity, but also its data-management features and built-in web-based API interface. Getting data into InfluxDB can be as easy as a web post, which places it within the reach of most internet-capable microcontrollers.

Kapacitor

Next up is our ‘K’. Kapacitor is a complex data processing engine that acts on data coming into your InfluxDB. It has several purposes, but the common use is to generate alerts based on data readings. Kapacitor supports a wide range of alert ‘endpoints’, from sending a simple email to alerting notification services like Pushover, or posting a message to the ubiquitous Slack. Multiple alerts to multiple destinations can be configured, and what constitutes an alert status is up to you. More advanced uses of Kapacitor include machine learning and anomaly detection.

Chronograf

The problem with Kapacitor is the configuration. It’s a lot of work with config files and the command line. Thoughtfully, InfluxData has created Chronograf, a graphical user interface to both Kapacitor and InfluxDB. If you prefer to keep away from the command line, you can query and manage your databases here as well as set up alerts, metrics that trigger an alert, and the configurations for the various handlers. This is all presented through a web app that you can access from anywhere on your network. You can also build ‘Dashboards’ – collections of charts displayed on a single page based on your InfluxDB data.

Telegraf

Finally, our ’T’ in TICK. One of the most common uses for time series databases is measuring computer performance. Telegraf provides the link between the machine it is installed on and InfluxDB. After a simple install, Telegraf will start logging all kinds of data about its host machine to your InfluxDB installation. Memory usage, CPU temperatures and load, disk space, and network performance can all be logged to your database and charted using Chronograf. This is more due to the Stack’s more common use for monitoring servers, but it’s still useful for making sure the brains of our network-of-things is working properly. If you get a problem, Kapacitor can not only trigger alerts but also user-defined scripts that may be able to remedy the situation.

Get HackSpace magazine issue 31 — out today

HackSpace magazine issue 31: on sale now!

You can read the rest of HackSpace magazine’s DIY IoT feature in issue 31, out today and available online from the Raspberry Pi Press online store. You can also download issue 31 for free.

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Share your keyboard and mouse between computers with Barrier

Declutter your desk by sharing your mouse and keyboard across multiple computers at once, including your Raspberry Pis, with Barrier. Raspberry Pi Director of Software Engineering, Gordon Hollingworth, shows you how.

Barrier walkthrough

Subscribe to our YouTube channel: http://rpf.io/ytsub Help us reach a wider audience by translating our video content: http://rpf.io/yttranslate Buy a Raspbe…

Desk clutter is a given

My desk is a bit untidy. Talking to people in our office, you’ll find that it’s mostly because I only clear it properly once a year, or leave it entirely until the next time we move office!

It’s cluttered with Raspberry Pis of random types, with little tags saying what’s wrong or right about each one, and then there’s every manner of SD card, adapter, JTAG connector, headphones, and whiteboard marker pens you can dream of filling the gaps.

But one thing that really annoys me is that I tend to have a mouse and keyboard per computer, and I’ve got at least four computers running at my desk at any one time.

Solutions to this problem have existed for a very long time, known as KVM (keyboard, video and mouse) switches; many people use these to switch (literally with a big toggle switch) between computer 1, 2, and 3 while using a single screen.

But if that’s what you want to do, the best solution is to use VNC on each of the computers so you can use a single display, keyboard, and mouse to access each of their screens and bring them all together.

And, that’s okay, but…

But that’s not quite what I want: I like having the mass-screen real-estate around me, and I like just glancing to the left to see my Raspberry Pi on its own screen.

If only there was a way to share my mouse and keyboard across multiple computers without having to flick switches or unplug USBs.

Well…

Barrier to the rescue!

In the same way one may set up multiple monitors for one computer, and move the mouse cursor seamlessly between them, Barrier allows you to share peripherals between multiple computers, allowing you to host your keyboard and mouse on one computer. It lets you simply drag your cursor from screen to screen, from device to device, as if by magic.

Download and set up Barrier

Barrier is free to use, and simple to set up. You can either follow the video tutorial shared above, or continue reading below:

Download barrier to your main computer

First, download and install Barrier from the developers’ installation page: github.com/debauchee/barrier/releases

At the end of the installation, the application will run. Select the Server option (the server is the one that has the keyboard and mouse that you want to share).

Next select Configure Server. Click on the computer screen in the top-right and drag it to where you want it to appear in relation to the server. It will default to being called ‘Unnamed’.

Next, double-click the new ‘Unnamed’ screen to set it up.

The only thing you need to do here is to set the screen name. Here I’ve changed it to ‘raspberrypi’.  Click OK here and on the Server configuration‘ dialogue. You’ll return to the main Barrier page. Click Reload.

Download Barrier to your Raspberry Pi computer

Now turn to your Raspberry Pi, open a terminal window (Ctrl-Alt-T if you didn’t know), and run:

sudo apt install barrier

Once installation is complete, Barrier should appear in the Accessories drop-down menu, which you can access via the main menu icon (the Raspberry Pi logo in the top right-hand corner). Select Barrier and, this time, choose Client.

If you leave Auto config selected, Barrier should just work, as long as the screen name is correct (you can change this by clicking Barrier and then Change settings) and matches the name you told the server.

And there you have it. You can now use your mouse and keyboard across both your computers. And, if you have enough desktop space for even more monitors, you can continue to add devices to Barrier until your room ends up looking something like this:

A man standing in front of a wall made of computer screens

If you use Barrier to clean up your workspace, make sure to share a ‘before’ and ‘after’ photo with us on Twitter.

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Make it rain chocolate with a Raspberry Pi-powered dispenser

This fully automated M&M’s-launching machine delivers chocolate on voice command, wherever you are in the room.

A quick lesson in physics

To get our head around Harrison McIntyre‘s project, first we need to understand parabolas. Harrison explains: “If we ignore air resistance, a parabola can be defined as the arc an object describes when launching through space. The shape of a parabolic arc is determined by three variables: the object’s departure angle; initial velocity; and acceleration due to gravity.”

Harrison uses a basketball shooter to illustrate parabolas

Lucky for us, gravity is always the same, so you really only have to worry about angle and velocity. You could also get away with only changing one variable and still be able to determine where a launched object will land. But adjusting both the angle and the velocity grants much greater precision, which is why Harrison’s machine controls both exit angle and velocity of the M&M’s.

Kit list

The M&M’s launcher comprises:

  • 2 Arduino Nanos
  • 1 Raspberry Pi 3
  • 3 servo motors
  • 2 motor drivers
  • 1 DC motor
  • 1 Hall effect limit switch
  • 2 voltage converters
  • 1 USB camera
  • “Lots” of 3D printed parts
  • 1 Amazon Echo Dot

A cordless drill battery is the primary power source.

The project relies on similar principles as a baseball pitching machine. A compliant wheel is attached to a shaft sitting a few millimetres above a feeder chute that can hold up to ten M&M’s. To launch an M&M’s piece, the machine spins up the shaft to around 1500 rpm, pushes an M&M’s piece into the wheel using a servo, and whoosh, your M&M’s piece takes flight.

Controlling velocity, angle and direction

To measure the velocity of the fly wheel in the machine, Harrison installed a Hall effect magnetic limit switch, which gets triggered every time it is near a magnet.

Two magnets were placed on opposite sides of the shaft, and these pass by the switch. By counting the time in between each pulse from the limit switch, the launcher determines how fast the fly wheel is spinning. In response, the microcontroller adjusts the motor output until the encoder reports the desired rpm. This is how the machine controls the speed at which the M&M’s pieces are fired.

Now, to control the angle at which the M&M’s pieces fly out of the machine, Harrison mounted the fly wheel assembly onto a turret with two degrees of freedom, driven by servos. The turret controls the angle at which the sweets are ‘pitched’, as well as the direction of the ‘pitch’.

So how does it know where I am?

With the angle, velocity, and direction at which the M&M’s pieces fly out of the machine taken care of, the last thing to determine is the expectant snack-eater’s location. For this, Harrison harnessed vision processing.


Harrison used a USB camera and a Python script running on Raspberry Pi 3 to determine when a human face comes into view of the machine, and to calculate how far away it is. The turret then rotates towards the face, the appropriate parabola is calculated, and an M&M’s piece is fired at the right angle and velocity to reach your mouth. Harrison even added facial recognition functionality so the machine only fires M&M’s pieces at his face. No one is stealing this guy’s candy!

So what’s Alexa for?

This project is topped off with a voice-activation element, courtesy of an Amazon Echo Dot, and a Python library called Sinric. This allowed Harrison to disguise his Raspberry Pi as a smart TV named ‘Chocolate’ and command Alexa to “increase the volume of ‘Chocolate’ by two” in order to get his machine to fire two M&M’s pieces at him.

       

Drawbacks

In his video, Harrison explaining that other snack-launching machines involve a spring-loaded throwing mechanism, which doesn’t let you determine the snack’s exit velocity. That means you have less control over how fast your snack goes and where it lands. The only drawback to Harrison’s model? His machine needs objects that are uniform in shape and size, which means no oddly shaped peanut M&M’s pieces for him.

He’s created quite the monster here, in that at first, the machine’s maximum firing speed was 40 mph. And no one wants crispy-shelled chocolate firing at their face at that speed. To keep his teeth safe, Harrison switched out the original motor for one with a lower rpm, which reduced the maximum exit velocity to a much more sensible 23 mph… Please make sure you test your own snack-firing machine outdoors before aiming it at someone’s face.

Go subscribe

Check out the end of Harrison’s videos for some more testing to see what his machine was capable of: he takes out an entire toy army and a LEGO Star Wars squad by firing M&M’s pieces at them. And remember to subscribe to his channel and like the video if you enjoyed what you saw, because that’s just a nice thing to do.

The post Make it rain chocolate with a Raspberry Pi-powered dispenser appeared first on Raspberry Pi.

Noticia Original

Coolest Projects goes online and everyone is welcome!

We’re thrilled that Coolest Projects is taking place this summer as an online showcase, and registration opens today!

A girl presenting a digital making project

Our world-leading technology fair usually takes place as a free face-to-face event, with thousands of young people coming together to showcase projects they’ve created. After making the tough decision to cancel the Coolest Projects 2020 events in Dublin and Manchester, we began building a solution that would allow us to host our tech showcase for young people online this year.

A boy presenting his digital making project

As so many young people are currently at home all over the world, we wanted to create an online space where they can share their tech projects, be inspired by their peers, and celebrate each other’s achievements as a community.

A chance to be creative and have fun

Coolest Projects is a great opportunity for young people to get creative, have fun, learn from others, and be a part of something truly special.

A girl presenting a digital making project

To get involved in Coolest Projects, all that young people need is an idea that involves tech, and the enthusiasm to bring it to life. If they’re looking for inspiration, they can explore our Digital Making at Home series of free, weekly code-along videos and step-by-step project guides. We’ve also got support for parents who want to learn more about the tools and programs their children could use to create a tech project.

We invite all creators and all project types!

Coolest Projects is open to anyone up to the age of 18, and young people can join wherever they are in the world. Creators at all levels of experience are encouraged, with projects from beginner to advanced, and it doesn’t matter whether the project is a work in progress, a prototype, or a finished product — every participant and every project are welcome!

A young person at a laptop

Young creators get to share their ideas with the world

All submitted projects will be showcased for the whole world to see in the new Coolest Projects online gallery, so that we can all celebrate the effort, enthusiasm, and creativity of young people who have turned an idea into reality using tech.

A boy working on a Raspberry Pi robot buggy

In the online gallery, you’ll be able to filter projects and explore at your leisure. We’ve enlisted some special judges to help us pick out favourites!

Why do young people take part in Coolest Projects?

Estela Liobikaitė from Strokestown, Co. Roscommon in Ireland took part in Coolest Projects International last year. She began coding at school with her teacher, Ms Gilleran, and developed a love for animation. Estela talks about the possibilities coding gives young people:

“I like coding because it is very entertaining to play to learn about technology. Coding gives a person many opportunities and possibilities.”

A teenage girl presenting a digital making project on a tablet

Estela at Coolest Projects International 2019

Sofia and Mihai, both aged 9, also took part in Coolest Projects International 2019. They travelled to the Dublin event from Slatina in Romania, where they attend a Code Club in their community. Sofia and Mihai both love animals and created their project, Friendship Saves Endangered Species, to raise awareness about the fragile ecosystem.

A girl and a boy holding up a book about coding

Sofia and Mihai at Coolest Projects 2019

Their advice for other young people thinking of getting involved in Coolest Projects is: “Follow your dream, put your ideas into practice, because Coolest Projects is a great opportunity!”

Get involved with Coolest Projects

If you know a young person who has made a digital creation, then encourage them to register it for Coolest Projects, be it an animation, website, game, app, robot, or anything else they’ve built with technology. Projects can be registered in the following categories: Hardware; Scratch; Mobile Apps; Websites; Games; Advanced Programming.

To register a project or find out more about taking part, visit coolestprojects.org. Registration closes on 28 June 2020.

 

PS This year’s Coolest Projects online showcase wouldn’t be possible without the support of our sponsors — thank you!

Platinum sponsors

Facebook, BNY Mellon, Liberty Global, Blizzard Entertainment, EPAM

Gold sponsors

Workday, Twitter

SME and community supporter

PayPal

The post Coolest Projects goes online and everyone is welcome! appeared first on Raspberry Pi.

Noticia Original

Control Panel

Pic School + Arduino Mega

/*
 * Arduino Keypad calculator Program
 */

#include <LiquidCrystal.h> //Header file for LCD from https://www.arduino.cc/en/Reference/LiquidCrystal
#include <Keypad.h> //Header file for Keypad from https://github.com/Chris--A/Keypad

const byte ROWS = 4; // Four rows
const byte COLS = 4; // Three columns

// Define the Keymap
char keys[ROWS][COLS] = {

  {'1','2','3','A'},

  {'4','5','6','B'},

  {'7','8','9','C'},

  {'*','0','#','D'}

};

int pinArray[] = {2, 3, 4, 5, 6, 7};
int count = 0;
int timer = 75;
// constants won't change. They're used here to set pin numbers:
const int buttonPin = 10;     // the number of the pushbutton pin
// variables will change:
int buttonState = 0; 

byte rowPins[ROWS] = { 33, 31, 29, 27 };// Connect keypad ROW0, ROW1, ROW2 and ROW3 to these Arduino pins.
byte colPins[COLS] = { 41, 39, 37, 35 }; // Connect keypad COL0, COL1 and COL2 to these Arduino pins.

Keypad kpd = Keypad( makeKeymap(keys), rowPins, colPins, ROWS, COLS ); //  Create the Keypad

const int rs = 43, en = 45, d4 = 47, d5 = 49, d6 = 51, d7 = 53; //Pins to which LCD is connected
LiquidCrystal lcd(rs, en, d4, d5, d6, d7);

 long Num1,Num2,Number;
 char key,action;
 boolean result = false;
 
void setup() {
  // we make all the declarations at once
  for (count=0;count<6;count++) {
    pinMode(pinArray[count], OUTPUT);
  }
  lcd.begin(16, 2); //We are using a 16*2 LCD display
  lcd.print("Ona's Calculator"); //Display a intro message
  lcd.setCursor(0, 1);   // set the cursor to column 0, line 1
  lcd.print("-V1.0"); //Display a intro message 

   delay(2000); //Wait for display to show info
    lcd.clear(); //Then clean it
}

void loop() {
buttonState = digitalRead(buttonPin);
key = kpd.getKey(); //storing pressed key value in a char

if (buttonState == HIGH) 
KnightRider();

if (key!=NO_KEY)
DetectButtons();

if (result==true)
CalculateResult();

DisplayResult();   
}

void DetectButtons()
{ 
     lcd.clear(); //Then clean it
    if (key=='*') //If cancel Button is pressed
    {Serial.println ("Button Cancel"); Number=Num1=Num2=0; result=false;}
    
     if (key == '1') //If Button 1 is pressed
    {Serial.println ("Button 1"); 
    if (Number==0)
    Number=1;
    else
    Number = (Number*10) + 1; //Pressed twice
    }
    
     if (key == '4') //If Button 4 is pressed
    {Serial.println ("Button 4"); 
    if (Number==0)
    Number=4;
    else
    Number = (Number*10) + 4; //Pressed twice
    }
    
     if (key == '7') //If Button 7 is pressed
    {Serial.println ("Button 7");
    if (Number==0)
    Number=7;
    else
    Number = (Number*10) + 7; //Pressed twice
    } 
  

    if (key == '0')
    {Serial.println ("Button 0"); //Button 0 is Pressed
    if (Number==0)
    Number=0;
    else
    Number = (Number*10) + 0; //Pressed twice
    }
    
     if (key == '2') //Button 2 is Pressed
    {Serial.println ("Button 2"); 
     if (Number==0)
    Number=2;
    else
    Number = (Number*10) + 2; //Pressed twice
    }
    
     if (key == '5')
    {Serial.println ("Button 5"); 
     if (Number==0)
    Number=5;
    else
    Number = (Number*10) + 5; //Pressed twice
    }
    
     if (key == '8')
    {Serial.println ("Button 8"); 
     if (Number==0)
    Number=8;
    else
    Number = (Number*10) + 8; //Pressed twice
    }   
  

    if (key == '#')
    {Serial.println ("Button Equal"); 
    Num2=Number;
    result = true;
    }
    
     if (key == '3')
    {Serial.println ("Button 3"); 
     if (Number==0)
    Number=3;
    else
    Number = (Number*10) + 3; //Pressed twice
    }
    
     if (key == '6')
    {Serial.println ("Button 6"); 
    if (Number==0)
    Number=6;
    else
    Number = (Number*10) + 6; //Pressed twice
    }
    
     if (key == '9')
    {Serial.println ("Button 9");
    if (Number==0)
    Number=9;
    else
    Number = (Number*10) + 9; //Pressed twice
    }  

      if (key == 'A' || key == 'B' || key == 'C' || key == 'D') //Detecting Buttons on Column 4
  {
    Num1 = Number;    
    Number =0;
    if (key == 'A')
    {Serial.println ("Addition"); action = '+';}
     if (key == 'B')
    {Serial.println ("Subtraction"); action = '-'; }
     if (key == 'C')
    {Serial.println ("Multiplication"); action = '*';}
     if (key == 'D')
    {Serial.println ("Devesion"); action = '/';}  

    delay(100);
  }
  
}

void CalculateResult()
{
  if (action=='+')
    Number = Num1+Num2;

  if (action=='-')
    Number = Num1-Num2;

  if (action=='*')
    Number = Num1*Num2;

  if (action=='/')
    Number = Num1/Num2; 
}

void DisplayResult()
{
  lcd.setCursor(0, 0);   // set the cursor to column 0, line 1
  lcd.print(Num1); lcd.print(action); lcd.print(Num2); 
  
  if (result==true)
  {lcd.print(" ="); lcd.print(Number);} //Display the result
  
  lcd.setCursor(0, 1);   // set the cursor to column 0, line 1
  lcd.print(Number); //Display the result
}

void KnightRider(){
  for (count=0;count<7;count++) {
   digitalWrite(pinArray[count], HIGH);
   delay(timer);
   digitalWrite(pinArray[count], LOW);
   
  }
  for (count=6;count>=0;count--) {
   digitalWrite(pinArray[count], HIGH);
   delay(timer);
   digitalWrite(pinArray[count], LOW);
   
  }
}