One of the best things about open source software is that, instead of being lost to the ravages of time like older proprietary software, anyone can dust off an old open source program and bring it up to the modern era. PyOBD, a python tool for interfacing with the OBD system in modern vehicles, was in just such a state with its latest version still being written in Python 2 which hasn’t had support in over three years. [barracuda-fsh] rewrote the entire program for Python 3 and included a few other upgrades to it as well.
Key feature updates with this version besides being completely rewritten in Python 3 include enhanced support for OBD-II commands as well as automating the detection of the vehicle’s computer capabilities. This makes the program much more plug-and-play than it would have been in the past. PyOBD now also includes the python-OBD library for handling the actual communication with the vehicle, while PyOBD provides the GUI for configuring and visualizing the data given to it from the vehicle. An ELM327 adapter is required.
With options for Mac, Windows, or Linux, most users will be able to make use of this software package provided they have the necessary ELM327 adapter to connect to their vehicle. OBD is a great tool as passenger vehicles become increasingly computer-driven as well, but there are some concerns surrounding privacy and security in some of the latest and proposed versions of the standard.
Browsing the Asian marketplaces online is always an experience. Sometimes, you see things at ridiculously low prices. Other times, you see things and wonder who is buying them and why — a shrimp pillow? But sometimes, you see something that probably could have a more useful purpose than the proposed use case.
That’s the case with the glut of “smart displays” you can find at very low prices. Ostensibly, these are being sold as system monitors. A business-card-sized LCD hooks up via USB and shows your CPU speed, temperature, and so on. Of course, this requires sketchy Windows software. I don’t run Windows, and if I did, I wouldn’t be keen to put some strange service on just so I could see tiny displays of my system information. But a 3.5-inch IPS LCD screen for $15 or less probably has some other uses. But how to drive it? Turns out, it is easier than you think and the hardware looks reasonably hackable, too.
Like a lot of this cheap stuff, these screens are sold under a variety of names, and apparently, there are some subtle differences. Two of the main makers of these screens are Turing and XuanFang, although you rarely see those names in the online listings. As you might expect, though, someone has reverse-engineered the protocol, and there is Python software that will replace the stock Windows software the devices use. Even better, there is an example of using the library for your own purposes.
If you’re interested in using Large Language Models (LLM) in a project, but aren’t plugged directly into the fast-developing world of artificial intelligence (AI), knowing what tool or software to use can be daunting. Luckily, [Max Woolf] created simpleaichat, which is complete with examples and documentation and minimal code complexity.
As [Max] puts it, the main motivations behind the project are to provide useful tools while making it easier for non-engineers to peer through the breathless hyperbole and see just how AI-based apps actually work. This project was directly inspired by [Max]’s own real-world software experiences in this area, particularly his frustrations with popular and much-hyped frameworks in which “Hello World” feels a lot more like Hell World.
simpleaichat is a Python package that provides easy and powerful ways to interface with the OpenAI API, makers of ChatGPT. Now, it is true that OpenAI’s models are not open source and access is not free, but they are easily one of the most capable and cost-effective services of their kind.
Prefer something a little more open, and a lot more private? There’s always the option to run an LLM locally on your own machine, possibly with the help of a tool like text-generation-webui or gpt4all. Running an LLM locally will not have the quality of OpenAI’s offerings, but it can still do the job. It’s also possible to give these local LLMs an interface that mimics OpenAI’s API, so there are loads of possibilities.
Are you getting ideas yet? Share them in the comments, or keep them to yourselves and submit a tip once your project is off the ground!
Jumperless is a jumperless breadboard with multicolored LED visualization of signals in real-time. Sounds like magic? This beautifully executed entry to the 2023 Hackaday Prize by [Kevin Santo Cappuccio] uses a boatload of CH446Q analog switch ICs to perform the interconnect between the Raspberry Pi Pico header and the jumper board (or breadboard if you prefer.)
This will add some significant resistance, but for low currents and digital logic levels, this should not be a major concern. Additionally, there are two DAC channels and four ADC channels to help break out of the digital world, which could make for some very interesting non-trivial applications.
The visualization of the Pico header signals is solved neatly with a tiny wishbone-shaped PCB that is reverse-mounted to the back of the main board to illuminate upwards. The masking of the labels is done by using copper to mask off the individual signals and solder mask to draw in the legends. This PCB-level hacking is simply wonderful to see. The PCBs are designed with KiCAD, the design files for which you can find here. It appears however that [Kevin] needed to have the spring clips for the jumper board custom-made, so you’d need to contact them if you needed to get some for a build.
On the software side of things, [Kevin] currently recommends using Wokwi, to run the Arduino stack applications and to perform the signal routing to the virtual jumper board. You can follow how it works internally here. A Python-based bridge application runs on the host computer, which takes care of programming the interconnects as they are constructed, which looking at the demo in the embedded video, appears to ‘just work.’
One word of caution though — the bridge app uses Python requests and Beautiful Soup to scrape the Wowki project page, which could potentially make it vulnerable to getting out-of-sync with updates, so hopefully [Kevin] will keep track of this and keep them in sync.
Modern microcontrollers like the RP2040 and ESP32 are truly a marvels of engineering. For literal pocket change you can get a chip that’s got a multi-core processor running at hundreds of megahertz, plenty of RAM, and more often than not, some form of wireless connectivity. Their capabilities have been nothing short of revolutionary for the DIY crowd — on any given day, you can see projects on these pages which simply wouldn’t have been possible back when the 8-bit Arduino was all most folks had access to.
Thanks to the increased performance of these MCUs, hackers and makers now even have a choice as to which programming language they want to use. While C is still the language of choice for processor-intensive tasks, for many applications, Python is now a viable option on a wide range of hardware.
This provides a far less intimidating experience for newcomers, not just because the language is more forgiving, but because it does away with the traditional compile-flash-pray workflow. Of course, that doesn’t mean the more experienced MCU wranglers aren’t invited to the party; they might just have to broaden their horizons a bit.
When looking for electronics projects to use in educational settings, there is no shortage of simple, lightweight, and easily-accessible systems to choose from. From robotic arms, drones, walking robots, and wheeled robots, there is a vast array of options. But as technology marches on, the robotics platforms need to keep up as well. This turtle-style wheeled robot called the Trundlebot uses the latest in affordable microcontrollers on a relatively simple, expandable platform for the most up-to-date educational experience.
The robot is built around a Raspberry Pi Pico, with two low-cost stepper motors to drive the wheeled platform. The chassis can be built out of any material that can be cut in a laser cutter, but for anyone without this sort of tool it is also fairly easy to cut the shapes out by hand. The robot’s functionality can be controlled through Python code, and it is compatible with the WizFi360-EVB-Pico which allows it to be remote controlled through a web application. The web interface allows easy programming of commands for the Trundlebot, including a drag-and-drop feature for controlling the robot.
With all of these features, wireless connectivity, and a modern microcontroller at the core, it is an excellent platform for educational robotics. From here it wouldn’t be too hard to develop line-follower robots, obstacle-avoiding robots, or maze-solving robots. Other components can easily be installed to facilitate these designs as well. If you’re looking for a different style robot, although not expressly for educational purposes this robotic arm can be produced for under $60.
There are a number of commercially-available robotic quadrupeds that can trace their heritage back to the MIT Mini Cheetah design, and one of them is the Unitree Go1 series which sports a distinctive X-shaped sensor cluster on its “face”. The basic models are affordable (as far as robots go, anyway) but Unitree claims only the high-priced EDU model can be controlled via the SDK. Happily, the Free Dog SDK provides a way to do exactly that.
The SDK is a work in progress, but fully usable and allows the user to send various high level and low level commands to the Go1 robots. High level examples include things like telling the robot to perform pushups, turn 90 degrees, or walk. Low level commands are things like specifying exact positions or torque levels for individual limbs. With the new SDK, doing those things programmatically is only a Python script away.
Know any other robots that might be based on the same system? This SDK might work on them, too.