LoRa is a wireless Radio frequency technology introduced by a company called Semtech intended to be used to transmit bi-directional information to a long-distance without consuming much power. If you are new to LoRa, then learn about LoRa and LoRaWAN Technology and check LoRa interfacing with Arduino and
We love the simplicity of Arduino for focused tasks, we love how Raspberry Pi GPIO pins open a doorway to a wide world of peripherals, and we love the software ecosystem of Intel’s x86 instruction set. It’s great that some products manage to combine all of them together into a single compact package, and we welcome the recent addition of Seeed Studio’s Odyssey X86J4105.
[Ars Technica] recently looked one over and found it impressive from the perspective of a small networked computer, but they didn’t dig too deeply into the maker-friendly side of the product. We can look at the product documentation to see some interesting details. This board is larger than a Raspberry Pi, but its GPIO pins were laid out in exactly the same order as that on a Pi. Some HATs could plug right in, eliminating all the electrical integration leaving just the software issue of ARM vs x86. Tasks that are not suitable for CPU-controlled GPIO (such as generating reliable PWM) can be offloaded to an on-board Arduino-compatible microcontroller. It is built around the SAMD21 chip, similar to the Arduino MKR and Arduino Zero but the pinout does not appear to match any of the popular Arduino form factors.
The Odyssey is not the first x86 single board computer (SBC) to have GPIO pins and an onboard Arduino assistant. LattePanda for example has been executing that game plan (minus the Raspberry Pi pin layout) for the past few years. We’ve followed them since their Kickstarter origins and we’ve featured creative uses here and there. LattePanda’s current offerings are built around Intel CPUs ranging from Atom to Core m3. The Odyssey’s Celeron is roughly in the middle of that range, and the SAMD21 is more capable than the ATmega32U4 (Arduino Leonardo) on board a LattePanda. We always love seeing more options in a market for us to find the right tradeoff to match a given project, and we look forward to the epic journeys yet to come.
The current COVID-19 scenario needs no introduction. While everyone is giving their best to move forward, it is important to act responsibly and tackle this problem collectively. Today in many public places and in other gatherings, it has become common to screen individuals for body temperature, as a preventive measure to check for fever. The device that is used to do this is called a Contactless Infrared Thermometer.
Gesture recognition and machine learning are getting a lot of air time these days, as people understand them more and begin to develop methods to implement them on many different platforms. Of course this allows easier access to people who can make use of the new tools beyond strictly academic or business environments. For example, rollerblading down the streets of Atlanta with a gesture-recognizing, streaming TV that [nate.damen] wears over his head.
He’s known as [atltvhead] and the TV he wears has a functional LED screen on the front. The whole setup reminds us a little of Deep Thought. The screen can display various animations which are controlled through Twitch chat as he streams his journeys around town. He wanted to add a little more interaction to the animations though and simplify his user interface, so he set up a gesture-sensing sleeve which can augment the animations based on how he’s moving his arm. He uses an Arduino in the arm sensor as well as a Raspberry Pi in the backpack to tie it all together, and he goes deep in the weeds explaining how to use Tensorflow to recognize the gestures. The video linked below shows a lot of his training runs for the machine learning system he used as well.
[nate.damen] didn’t stop at the cheerful TV head either. He also wears a backpack that displays uplifting messages to people as he passes them by on his rollerblades, not wanting to leave out those who don’t get to see him coming. We think this is a great uplifting project, and the amount of work that went into getting the gesture recognition machine learning algorithm right is impressive on its own. If you’re new to Tensorflow, though, we have featured some projects that can do reliable object recognition using little more than a Raspberry Pi and a camera.
Arduino and Google are excited to announce that the Google Science Journal will be transferring from Google to Arduino this September. Due to Arduino's existing experience with the Science Journal and a long-standing commitment to open source and hands-on science, Google has agreed to transfer ownership of the open-source project over to Arduino.
Who doesn’t love robotic spiders? Today’s biomimetic robot comes in the form of Miles, the quadruped spider robot from [_Robox].
Miles uses twelve servos to control its motion, three on each of its legs, and also includes a standard HC-SR04 ultrasonic distance sensor for some obstacle avoidance capabilities. Twelve servos can use quite a bit of power, so [_Robox_] had to power Miles with six LM7805 ICs to get sufficient current. [_Robox_] laser cut acrylic sheets for Miles’s body but mentions that 3D printing would work as well.
Miles uses inverse kinematics to get around, which we’ve seen in a previous project and is a pretty popular technique for controlling robotic motion. The Instructable is a little light on the details, but the source code is something to take a look at. In addition to simply moving around [_Robox_] developed code to make Miles dance, wave, and take a bow. That’s sure to be a hit at your next virtual show-and-tell.
By now you’re saying “wait, spiders have eight legs”, and of course you’re right. But that’s an awful lot of servos. Anyway, if you’d rather 3D print your four-legged spider, we have a suggestion.
Despite being cooked up by Compuserve back in the late 1980s, GIFs have seen a resurgence on the modern internet, mostly because they’re fun. However, all our small embedded systems are getting color screens these days, and they’d love to join in the party. [Larry Bank] has whipped up a solution for just that reason, letting embedded systems play back short animated GIFs with limited resources.
[Larry] does a great job of explaining how the GIF format works, using LZW compression and variable-length codes. He talks about how the design of the format presents challenges, particularly when working with microcontrollers. Despite this, the final code works well, and is able to work with most animated GIFs of the right dimensions and construction. 24K of RAM is required, and image width is limited to 320 pixels. Images can be loaded from flash, memory, or SD cards, and he notes that best performance is gained with a microcontroller with fast SPI for writing to screens quickly.
It’s a great piece of software that promises to add a lot of charm, or silliness, to microcontroller projects. It also simplifies the use of animations, which can now be designed on computers rather than by using onboard graphics libraries. GIF really is the format that never seems to die; we’ve featured cameras dedicated to the form before. Video after the break.
I built two of these boards now and they both react the same way . The current dooes not start reading until my load reaches 1700ma and it only reads .11amps any lower load and the current draw is 0.00. The schetch compiles and loads fine but the hardware does not work properly. changed both the mcp4921 and the opamp. No affect. Anyone have an idea what might be going on
suspect it might be the program, but a little week in that department. Help!