Safely catching mice is a better way of fixing a problem, and using Raspberry Pi means it needs less supervision. In the new issue of The MagPi magazine, Rob Zwetsloot takes a look with the maker, Andrew Taylor.
With some IoT projects, it’s the little things that help. For example, take Andrew Taylor, who did the good thing of setting up a humane mousetrap. However, checking it to see if any mice had been caught in it, while necessary, was getting a little boring.
There’s one major component to the setup, which is the PIR sensor
“If a mouse had gone in and I did not check it, the mouse would quickly run out of food and water!” Andrew tells us. “Having been interested in Raspberry Pi for a couple of years and having recently begun learning Python using the Enviro+ environment sensors, I figured a Raspberry Pi with a motion sensor would be an ideal way to check.”
It’s a fairly simple setup, one commonly used in CCTV builds and some fun ‘parent detectors’ on the Raspberry Pi Foundation’s projects site.
An old coffee tub is used as a case for the sensor, a good way to recycle
Mouse motion
“I came across a couple of automated mousetraps that people had made from scratch, but wanting to keep it simple and cheap,” Andrew explains. “I wanted to use off-the-shelf parts where possible and keep costs down. The Pi Hut had a tutorial for a DIY burglar alarm utilising a PIR sensor, IFTTT, and Pushbullet, which seemed like an ideal starting point.”
A Raspberry Pi Zero is used to check the motion sensor and send data if it’s activated
IFTTT – If This Then That – is an online service popular with IoT folks. It’s great for small things like cross-posting images on social media services, or sending a push notification when motion is detected in a mousetrap.
“I have only had one mouse since, but it worked!” Andrew says. “I was averaging about 800 detections a day and suddenly got well over a 1000. Sure enough, there was a mouse in the trap which I released shortly afterwards. I do tend to notice that the values fluctuate a bit, so it is always worth checking over the previous day’s results to see if it is notably higher.”
Wiring up the PIR to Raspberry Pi is quite simple, and means the project is easy to maintain
You might think that 800 push notifications a day is far worse than just occasionally checking your garage, and you’d be right, so Andrew tweaked the code a bit: “The code examples I found sent a notification for each movement detection – which I knew would be rather annoying, considering how randomly PIR sensors sometimes seem to trigger. My script instead logs any hits at a max of 1 per 30 seconds and then triggers a notification once every 24 hours, meaning I just get one notification a day.”
It’s a simple design, and was kept simple to keep to a small budget
Beat a path
There’s always room for improvement, as Andrew explains: “I intend to improve the code so that it can record running averages and give an indication as to whether it believes there has been a significant spike that might necessitate me checking it out.”
The first successful capture was released back outside the garage
Whilst the aim of the project was to keep costs down, Andrew is tempted to experiment by adding a camera, and possibly a light, so he can have a peek remotely when there has been a spike in the readings and to see if it is a false alarm. Which, as he admits, is “a new height in laziness!”
The MagPi #108 out NOW!
You can grab the brand-new issue right now from the Raspberry Pi Press store, or via our app on Android or iOS. You can also pick it up from supermarkets and newsagents. There’s also a free PDF you can download.
A recent Forbes article reported that over the last four years, the use of artificial intelligence (AI) tools in many business sectors has grown by 270%. AI has a history dating back to Alan Turing’s work in the 1940s, and we can define AI as the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.
Recent advances in computing technology have accelerated the rate at which AI and data science tools are coming to be used.
Four key areas of AI are machine learning, robotics, computer vision, and natural language processing. Other advances in computing technology mean we can now store and efficiently analyse colossal amounts of data (big data); consequently, data science was formed as an interdisciplinary field combining mathematics, statistics, and computer science. Data science is often presented as intertwined with machine learning, as data scientists commonly use machine learning techniques in their analysis.
Computer science, AI, statistics, machine learning, and data science are overlapping fields. (Diagram from our forthcoming free online course about machine learning for educators)
AI impacts everyone, so we need to teach young people about it
AI and data science have recently received huge amounts of attention in the media, as machine learning systems are now used to make decisions in areas such as healthcare, finance, and employment. These AI technologies cause many ethical issues, for example as explored in the film Coded Bias. This film describes the fallout of researcher Joy Buolamwini’s discovery that facial recognition systems do not identify dark-skinned faces accurately, and her journey to push for the first-ever piece of legislation in the USA to govern against bias in the algorithms that impact our lives. Many other ethical issues concerning AI exist and, as highlighted by UNESCO’s examples of AI’s ethical dilemmas, they impact each and every one of us.
We need to make sure that young people understand AI technologies and how they impact society and individuals.
So how do such advances in technology impact the education of young people? In the UK, a recent Royal Society report on machine learning recommended that schools should “ensure that key concepts in machine learning are taught to those who will be users, developers, and citizens” — in other words, every child. The AI Roadmap published by the UK AI Council in 2020 declared that “a comprehensive programme aimed at all teachers and with a clear deadline for completion would enable every teacher confidently to get to grips with AI concepts in ways that are relevant to their own teaching.” As of yet, very few countries have incorporated any study of AI and data science in their school curricula or computing programmes of study.
Our seminar speakers will share findings on how teachers can help their learners get to grips with AI concepts.
Partnering with The Alan Turing Institute for a new seminar series
Everyone with an interest in computing education research is welcome at our seminars, from researchers to educators and students!
The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence and does pioneering work in data science research and education. The Institute conducts many different strands of research in this area and has a special interest group focused on data science education. As such, our partnership around the seminar series enables us to explore our mutual interest in the needs of young people relating to these technologies.
This promises to be an outstanding series drawing from international experts who will share examples of pedagogic best practice […].
Dr Matt Forshaw, The Alan Turing Institute
Dr Matt Forshaw, National Skills Lead at The Alan Turing Institute and Senior Lecturer in Data Science at Newcastle University, says: “We are delighted to partner with the Raspberry Pi Foundation to bring you this seminar series on AI, machine learning, and data science. This promises to be an outstanding series drawing from international experts who will share examples of pedagogic best practice and cover critical topics in education, highlighting ethical, fair, and safe use of these emerging technologies.”
Our free seminar series about AI, machine learning, and data science
At our computing education research seminars, we hear from a range of experts in the field and build an international community of researchers, practitioners, and educators interested in this important area. Our new free series of seminars runs from September 2021 to February 2022, with some excellent and inspirational speakers:
Tues 7 September:Dr Mhairi Aitken from The Alan Turing Institute will share a talk about AI ethics, setting out key ethical principles and how they apply to AI before discussing the ways in which these relate to children and young people.
Tues 5 October:Professor Carsten Schulte, Yannik Fleischer, and Lukas Höper from Paderborn University in Germany will use a series of examples from their ProDaBi programme to explore whether and how AI and machine learning should be taught differently from other topics in the computer science curriculum at school. The speakers will suggest that these topics require a paradigm shift for some teachers, and that this shift has to do with the changed role of algorithms and data, and of the societal context.
Tues 3 November:Professor Matti Tedre and Dr Henriikka Vartiainen from the University of Eastern Finland will focus on machine learning in the school curriculum. Their talk will map the emerging trajectories in educational practice, theory, and technology related to teaching machine learning in K-12 education.
Tues 7 December: Professor Rose Luckin from University College London will be looking at the breadth of issues impacting the teaching and learning of AI.
Tues 11 January: We’re delighted that Dr Dave Touretzky and Dr Fred Martin (Carnegie Mellon University and University of Massachusetts Lowell, respectively) from the AI4K12 Initiative in the USA will present some of the key insights into AI that the researchers hope children will acquire, and how they see K-12 AI education evolving over the next few years.
Tues 1 February: Speaker to be confirmed
How you can join our online seminars
All seminars start at 17:00 UK time (18:00 Central European Time, 12 noon Eastern Time, 9:00 Pacific Time) and take place in an online format, with a presentation, breakout discussion groups, and a whole-group Q&A.
Befinitiv has built a custom film cartridge, using a Raspberry Pi Zero W, that turned their gorgeous old analogue camera into a digital one, and enabled it to take digital photos, videos, and even wirelessly live stream to the Internet.
A quick, simple build video for a smooth-running project
The analogue camera they used in the build was considered state-of-the-art around fifty years ago, but it lives on to capture another day, all thanks to a tiny computer we made just a few years ago.
It’s a beauty
The maker replaced the old-fashioned camera film roll with a digital cartridge housing a tiny Raspberry Pi camera — with the lens removed — and a Raspberry Pi Zero W. The housing was designed to fit in the back of the camera where original photographers would have clipped the film roll in, and then spooled it over.
Designed to fit
Along with the camera and the Raspberry Pi Zero W, the custom-built cartridge also houses a LiPo battery and a DC to DC converter, used to boost the power supply to the Raspberry Pi up to +5V.
Teeny tech packed into a teeny space
The whole project took just two hours to complete from start to finish, everything worked first time. Befinitiv had wanted to use the Raspberry Pi High Quality Camera, but space inside the housing was just too tight. Maybe next time? Perhaps they can use one of those giant ancient cameras, where the photographer had to flip a blanket over their head, all while holding a stick in the air with the flash.
This old analogue camera is now fully digital
More retro projects from the maker
Fancy more where this retrofit goodness came from? The maker has also upgraded a flip phone from the year 2000. Oh! I just realised the year 2000 was more than 20 years ago. Watch the build video while I go and burn all of my skater boy jeans and slogan t-shirts…
Don’t let your old flip phone die
They also did something weird but cool sounding with this noisy teletype machine. Is it a teletype machine? What’s a teletype machine? I saw a fax machine once..?
We love seeing all the wonderful things people are doing in the community — that’s why we’re sharing our new series of short films documenting some of the incredible journeys of community members in all corners of the globe!
Laura found her peer group at a local CoderDojo and has travelled the world with her friends and the robots they have built together.
Today we bring you the third wonderful film in this series of community stories. For the series, we’ve been super lucky to collaborate with digital makers all over the world, and today’s story exemplifies how truly global the community is.
Watch our video to find out how this ambitious young digital maker’s passion for creating with technology has propelled her around the world!
Say hi to Laura
Laura’s journey began in her hometown of Timișoara, Romania. In Laura’s words: “I joined my local CoderDojo, and it changed my life.”
Laura (17) started attending her CoderDojo coding club four years ago because she loves problem-solving and wanted to learn more about how digital technology works. Her biggest discovery at CoderDojo, however, was the other young people there, who were just as passionate about technology as she was. Laura says, “I had the opportunity to meet people with the same interests. Everybody was working, exchanging ideas, having fun!”
Laura and the new friends she made worked together to solve problems in their local community: they built an autonomous waste-collecting robot and a drone-mounted air pollution monitor.
“I want to bring a change to the world.”
Laura
But Laura’s tech journey did not stop there. In 2017, she travelled to Dublin to present her latest project — a Raspberry Pi-powered, mind-controlled robot! — at Coolest Projects International, which introduced her to a global community of digital makers. And since then she’s even taken part in a robotics competition at MIT!
At Coolest Projects International 2017, Laura demonstrated her mind-controlled robot to our CEO Philip — she said the robot worked really well with Philip because he has no hair!
Working alongside like-minded peers and connecting with a global community of young tech creators has had a profound impact on Laura. She says, “I never imagined that I would have so many opportunities to travel, expand my horizons, and meet so many people. It’s thanks to CoderDojo and Coolest Projects that I’ve been able to build an amazing network of friends, and together we’re ready to take on the world.”
We are so excited to see what Laura will do next. Help us celebrate Laura by liking and sharing her story on Twitter, Linkedin, or Facebook!
When we saw Alex Glow’s name in the latest issue of HackSpace magazine, we just had to share their project. HackSpace #45 celebrates the best Raspberry Pi builds of all time, and we remembered spotting Alex’s wearable robotic owl familiar back in the day. For those of you yet to have had the pleasure, meet Archimedes…
Archimedes taking a perch on his maker’s shoulder
Back in 2018, Hackster’s Alex Glow built Archimedes, an incredible robot companion using a combination of Raspberry Pi Zero W and Arduino with the Google AIY Vision Kit for its ‘brain’.
An updated model, Archie 2, using Raspberry Pi 3B, ESP32-powered Matrix Voice, and an SG90 micro-servo motor saw the personable owl familiar toughen up – Alex says the 3D-printed case is far more durable – as well as having better voice interaction options using Matrix HAL (for which installer packages are provided for Raspberry Pi and Python), plus Mycroft and Snips.ai voice assistant software.
Owl innards
Other refinements included incorporating compact discs into the owl’s wings to provide an iridescent sheen. Slots in the case allowed Alex to feed through cable ties to attach Archie’s wings, which she says now “provide a lively bounce to the wings, in tune with his active movements (as well as my own).”
Raspberry Pi getting stuffed into Archimedes’ head
