Tag Archives: Raspberry Pi 3B+

Meet SeedGerm: a Raspberry Pi-based platform for automated seed imaging

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Researchers at the John Innes Centre for plant and microbial science were looking for a cost‐effective phenotyping platform for automated seed imaging. They figured a machine learning-driven image analysis was the quickest way to deliver this essential, yet challenging, aspect of agricultural research. Sounds complicated, but they found that our tiny computers could handle it all.

Two types of SeedGerm hardware with wired and wireless connectivity used for acquiring seed germination image series for different crop species
Two types of SeedGerm hardware with wired and wireless connectivity used for acquiring seed germination image series for different crop species

What is phenotyping?

A phenotype is an organism’s observable characteristics, like growing towards the light, or having a stripy tail, or being one of those people who can make their tongue roll up. An organism’s phenotype is the result of the genetic characteristics it has – its genotype – and the environment in which it lives. For example, a plant’s genotype might mean it can grow quickly and become tall, but if its environment lacks water, it’s likely to have a slow-growing and short phenotype.

Phenotyping means finding out and recording particular aspects of an organism’s phenotype: for example, how fast seeds germinate, or how broad a plant’s leaves are.

Why do seeds need phenotyping?

Phenotyping allows us to guess at a seed’s genotype, based on things we can observe about the seed’s phenotype, such as its size and shape.

We can study which seed phenotypes appear to be linked to desirable crop phenotypes, such as a high germination rate, or the ability to survive in dry conditions; in other words, we can make predictions about which seeds are likely to grow into good crops. And if we have controlled the environment in which we’re doing this research, we can be reasonably confident that these “good” seed phenotypes are mostly due not to variation in environmental conditions, but to properties of the seeds themselves: their genotype.

Close up of seed germ set up 1
A close up of the incubators, each with Raspberry Pi computers on top, running the show

Growers need seeds that germinate effectively and uniformly to maximise crop productivity, so seed suppliers are interested in making sure their samples meet a certain germination rate.

The phenotypic traits that are used to work out whether seeds are likely to be good for growers are listed in the full research paper. But in general, researchers are looking for things like width, length, roundness, and contour lines in seeds.

How does Raspberry Pi help?

Gathering observations for phenotyping is a difficult and time-consuming process, and in order to capture high‐quality seed imaging continuously, the team needed to design two types of hardware apparatus. Raspberry Pi computers (Raspberry Pi 2 Model B or Raspberry Pi 3 Model B+) power both SeedGerm hardware designs, with a Raspberry Pi camera also providing image data in the lower-cost design.

seed genotyping at a computer
The open source software at work next to one of the mini seed incubators

The brilliant team behind this project recognised the limitations of current seed imaging approaches, and looked to explore how automating the analysis of seed germination could scale up their work in an affordable way. The SeedGerm system benefits from the cost-effectiveness of Raspberry Pi hardware and the open source software the team chose, and that makes us super happy.

Read the whole research paper, published in New Phytologist, here.

Raspberry Pi in biological sciences

Dr Jolle Jolles, a behavioural ecologist at the Center for Ecological Research and Forestry Applications (CREAF) near Barcelona, Spain, and a passionate Raspberry Pi user, has recently published a detailed review of the uptake of Raspberry Pi in biological sciences. He found that well over a hundred published studies have made use of Raspberry Pi hardware in some way.

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Global sunrise/sunset Raspberry Pi art installation

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24h Sunrise/Sunset is a digital art installation that displays a live sunset and sunrise happening somewhere in the world with the use of CCTV.

Image by fotoswiss.com

Artist Dries Depoorter wanted to prove that “CCTV cameras can show something beautiful”, and turned to Raspberry Pi to power this global project.

Image by fotoswiss.com

Harnessing CCTV

The arresting visuals are beamed to viewers using two Raspberry Pi 3B+ computers and an Arduino Nano Every that stream internet protocol (IP) cameras with the use of command line media player OMXPlayer.

Dual Raspberry Pi power

The two Raspberry Pis communicate with each other using the MQTT protocol — a standard messaging protocol for the Internet of Things (IoT) that’s ideal for connecting remote devices with a small code footprint and minimal network bandwidth.

One of the Raspberry Pis checks at which location in the world a sunrise or sunset is happening and streams the closest CCTV camera.

The insides of the sleek display screen…

Beam me out, Scotty

The big screens are connected with the I2C protocol to the Arduino, and the Arduino is connected serial with the second Raspberry Pi. Dries also made a custom printed circuit board (PCB) so the build looks cleaner.

All that hardware is powered by an industrial power supply, just because Dries liked the style of it.

Software

Everything is written in Python 3, and Dries harnessed the Python 3 libraries BeautifulSoup, Sun, Geopy, and Pytz to calculate sunrise and sunset times at specific locations. Google Firebase databases in the cloud help with admin by way of saving timestamps and the IP addresses of the cameras.

Hardware

The artist stood infront of the two large display screens
Image of the artist with his work by fotoswiss.com

And, lastly, Dries requested a shoutout for his favourite local Raspberry Pi shop Gotron in Ghent.

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Give your voice assistant a retro Raspberry Pi makeover

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Do you feel weird asking the weather or seeking advice from a faceless device? Would you feel better about talking to a classic 1978 2-XL educational robot from Mego Corporation? Matt over at element14 Community, where tons of interesting stuff happens, has got your back.

Watch Matt explain how the 2-XL toy robot worked before he started tinkering with it. This robot works with Google Assistant on a Raspberry Pi, and answers to a custom wake word.

Kit list

Our recent blog about repurposing a Furby as a voice assistant device would have excited Noughties kids, but this one is mostly for our beautiful 1970s- and 1980s-born fanbase.

Time travel

2-XL, Wikipedia tells us, is considered the first “smart toy”, marketed way back in 1978, and exhibiting “rudimentary intelligence, memory, gameplay, and responsiveness”. 2-XL had a personality that kept kids’ attention, telling jokes and offering verbal support as they learned.

Teardown

Delve under the robot’s armour to see how the toy was built, understand the basic working mechanism, and watch Matt attempt to diagnose why his 2-XL is not working.

Setting up Google Assistant

The Matrix Creator daughter board mentioned in the kit list is an ideal platform for developing your own AI assistant. It’s the daughter board’s 8-microphone array that makes it so brilliant for this task. Learn how to set up Google Assistant on the Matrix board in this video.

What if you don’t want to wake your retrofit voice assistant in the same way as all the other less dedicated users, the ones who didn’t spend hours of love and care refurbishing an old device? Instead of having your homemade voice assistant answer to “OK Google” or “Alexa”, you can train it to recognise a phrase of your choice. In this tutorial, Matt shows you how to set up a custom wake word with your voice assistant, using word detection software called Snowboy.

Keep an eye on element14 on YouTube for the next instalment of this excellent retrofit project.

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Self-driving trash can controlled by Raspberry Pi

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YouTuber extraordinaire Ahad Cove HATES taking out the rubbish, so he decided to hack a rubbish bin/trash can – let’s go with trash can from now on – to take itself out to be picked up.

Sounds simple enough? The catch is that Ahad wanted to create an AI that can see when the garbage truck is approaching his house and trigger the garage door to open, then tell the trash can to drive itself out and stop in the right place. This way, Ahad doesn’t need to wake up early enough to spot the truck and manually trigger the trash can to drive itself.

Hardware

The trash can’s original wheels weren’t enough on their own, so Ahad brought in an electronic scooter wheel with a hub motor, powered by a 36V lithium ion battery, to guide and pull them. Check out this part of the video to hear how tricky it was for Ahad to install a braking system using a very strong servo motor.

The new wheel sits at the front of the trash can and drags the original wheels at the back along with

An affordable driver board controls the speed, power, and braking system of the garbage can.

The driver board

Tying everything together is a Raspberry Pi 3B+. Ahad uses one of the GPIO pins on the Raspberry Pi to send the signal to the driver board. He started off the project with a Raspberry Pi Zero W, but found that it was too fiddly to get it to handle the crazy braking power needed to stop the garbage can on his sloped driveway.

The Raspberry Pi Zero W, which ended up getting replaced in an upgrade

Everything is kept together and dry with a plastic snap-close food container Ahad lifted from his wife’s kitchen collection. Ssh, don’t tell.

Software

Ahad uses an object detection machine learning model to spot when the garbage truck passes his house. He handles this part of the project with an Nvidia Jetson Xavier NX board, connected to a webcam positioned to look out of the window watching for garbage trucks.

Object detected!

Opening the garage door

Ahad’s garage door has a wireless internet connection, so he connected the door to an app that communicates with his home assistant device. The app opens the garage door when the webcam and object detection software see the garbage truck turning into his street. All this works with the kit inside the trash can to get it to drive itself out to the end of Ahad’s driveway.

There she goes! (With her homemade paparazzi setup behind her)

Check out the end of Ahad’s YouTube video to see how human error managed to put a comical damper on the maiden voyage of this epic build.

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Raspberry Pi Off-World Bartender

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Three things we like: Blade Runner, robots, and cocktails. That’s why we LOVE Donald Bell‘s Raspberry Pi–packed ‘VK-01 Off-World Bartender‘ cocktail making machine.

This machine was due to be Donald’s entry into the Cocktail Robotics Grand Challenge, an annual event in San Francisco. By the time the event was cancelled, he was too deep into his awesome build to give up, so he decided to share it with the Instructables community instead.

Donald wanted users to get as much interaction and feedback as possible, rather than simply pressing a button and receiving a random drink. So with this machine, the interaction comes in four ways: instructions provided on the screen, using a key card to bypass security, placing and removing a cup on the tray, and entering an order number on the keypad.

In addition to that, feedback is provided by way of lighting changes, music, video dialogue, pump motors whirring, and even the clicks of relays at each stage of the cocktail making process.

Ordering on the keypad

close up of the black keypad

The keypad allows people to punch in a number to trigger their order, like on a vending machine. The drink order is sent to the Hello Drinkbot software running on the Raspberry Pi 3B that controls the pumps.

Getting your cup filled

Inside the cup dispenser sensor showing the switch and LEDs
The switch under the lid and ring of LEDs on the base

In order for the machine to be able to tell when a vessel is placed under the dispenser spout, and when it’s removed, Donald built in a switch under a 3D-printed tray. Provided the vessel has at least one ice cube in it, even the lightest plastic up is heavy enough to trigger the switch.

The RFID card reader

Cocktail machine customers are asked to scan a special ID card to start. To make this work, Donald adapted a sample script that blinks the card reader’s internal LED when any RFID card is detected.

Interactive video screen

close up of the interactive screen on the machine showing Japanese style script

This bit is made possible by MP4Museum, a “bare-bones” kiosk video player software that the second Raspberry Pi inside the machine runs on boot. By connecting a switch to the Raspberry Pi’s GPIO, Donald enabled customers to advance through the videos one by one. And yes, that’s an official Raspberry Pi Touch Display.

Behind the scenes of the interactive screen with the Raspberry Pi wired up
Behind the scenes of the screen with the Raspberry Pi A+ running the show

The Hello Drinkbot ‘bartender’

screen grab of the hello drinkbot web interface

Donald used the Python-based Hello Drinkbot software as the brains of the machine. With it, you can configure which liquors or juices are connected to which pumps, and send instructions on exactly how much to pour of each ingredient. Everything is configured via a web interface.

Via a bank of relays, microcontrollers connect all the signals from the Touch Display, keypad, RFID card reader, and switch under the spout.

Here’s the Fritzing diagram for this beast

Supplies

Donald shared an exhaustive kit list on his original post, but basically, what you’re looking at is…

Pencil sketches of the machine from different angles
Donald’s friend Jim Burke‘s beautiful concept sketches

And finally, check out the Raspberry Pi–based Hello Drinkbot project by Rich Gibson, which inspired Donald’s build.

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Steampunk ‘Help is coming’ Raspberry Pi alert system

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Tom Lee decided to combine his household with his sister-in-law during lockdown so that she could help him make childcare more manageable. The problem was, Tom’s household was a smidge frantic in the mornings, as the family struggled to be up and ready in time for his sister-in-law’s arrival.

Enter this Raspberry Pi–powered tracking device, which tells Tom when the family car is on its way with childcare support. The DIY appliance helps his household manage childcare routines like clockwork.

The magic is in the wooden box, but the light cage and electrical meter are all part of the show

When the family car is moving, a light turns on, and an antique electrical meter points to 30…20…10 to show the estimated minutes until the driver arrives. The movements of the car come in from a cellular Sinotrack OBD2 dongle pointed at a traccar server running on Raspberry Pi 3.

We see you in there, Raspberry Pi…

Tom explains: “I have not found traccar to be the greatest to work with, but you can make it forward everything it decodes to your own script pretty easily.”

Materials:

  • Arduino microcontrollers (ATMega328P & ESP8266 based)
  • Raspberry Pi (Model 1 and 3)
  • Dongle device in car (with SIM card and cellular service)
  • Light device with bulb and solid state relay
  • Antique electrical meter (for the steampunks among you – any similar device will do the job!) 
The light safety cage was rescued from an old workshop

The case (below) is a lasercut design Tom had made by online laser cutting business Ponoko.

Inside there’s a solid state relay and a first-generation Raspberry Pi (hidden under the black cable in the photo below). This Raspberry Pi model doesn’t have wireless connectivity, and Tom found that getting wireless working was a bit tricky for this project.

Tom produced a nice long webinar to show you exactly how this all works. So if you’d like to give this project a try, watch it for yourself.

You’ll learn how to…

Code resources

Oh, and he’s only gone and uploaded every single bit of code you’ll need on GitHub (what an angel):

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