GPS Overlays Give Real Life Racing A Video Game Feel

Racing is certainly exciting for the person rocketing around the track fast enough to get the speedometer into the triple digits, and tends to be a decent thrill for the spectators if they’ve got good seats. But if you’re just watching raw race videos on YouTube from the comfort of your office chair it can be a bit difficult to appreciate. There’s a lack of context for the viewer, and it can be hard to get the same sense of speed and position that you’d have if you saw the event first hand.

In an effort to give his father’s racing videos a bit more punch, [DusteD] came up with a clever way of adding video game style overlays to the recordings. The system provides real-time speed, lap times, and even a miniature representation of the track complete with a marker to show where the action is taking place. The end result is that recordings of Dad’s exploits on the track could pass as gameplay footage from Gran Turismo (we know GT doesn’t have motorcycles, but you get the idea).

The first part of the system is the tracker itself, which consists of a GPS receiver, an Arduino Pro Micro, and an SD card module. [DusteD] powers the device with two 18650 cells in parallel, and a DC-DC boost converter to step it up to 5V. Everything is contained in a 3D printed enclosure that he designed in OpenSCAD, with the only external elements being a toggle switch, a momentary switch, and most critically, a set of LEDs.

These LEDs play into the second part of the system, the software. The blinking LEDs are positioned so they’ll get picked up by the camera, which is then used to help synchronize the data stored on the SD card with the video. [DusteD] came up with some software that will take the speed and position information from the card, and turn it into PNG files with transparent backgrounds. These are then placed on top of the video with the help of FFmpeg. It takes a little adjustment to get everything lined up properly, but as the video after the break shows the end result is very impressive.

This build reminds us of the Raspberry Pi powered GPS helmet camera we featured a few years back, and it’s interesting to see how the two projects achieved what’s essentially the same goal in different ways.

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Electric Bike From The Ground Up

Electric vehicles are getting more traction these days, but this trend is rolling towards us in more ways than just passenger vehicles. More and more bikes are being electrified too, since the cost of batteries has come down and people realize that they can get around town easily without having to pay the exorbitant price to own, fuel, and maintain a car. Of course there are turnkey ebikes, but those don’t interest us much around here. This ebike from [Andy] is a master class in how to build your own ebike.

Due to some health issues, [Andy] needed a little bit of assistance from an electric motor on his bike, but found out that the one he wanted wouldn’t fit his current bike quite right. He bought a frame from eBay with the right dimensions and assembled the bike from scratch. Not only that, but when it was time to put the battery together he sourced individual 18650 cells and built a custom battery for the bike. His build goes into great detail on how to do all of these things, so even if you need a lithium battery for another project this build might be worth a read.

If you’ve never been on an electric bike before, they’re a lot of fun to ride. They’re also extremely economical, and a good project too if you’re looking for an excuse to go buy a kit and get to work. You can get creative with the drivetrain too if you’d like to do something out of the box, such as this bike that was powered by AA batteries and a supercapacitor.

Hands On With Python 3.7: What’s New In The Latest Release

Used for general purpose programming, data science, website backends, GUIs, and pretty much everything else; the first programming language for many, and claimed to be the fastest growing in the world, is of course Python. The newest version 3.7.0 has just recently been released.
Naturally any release of Python, no matter how small, undergoes meticulous planning and design before any development is started at all. In fact, you can read the PEP (Python Enhancement Proposal) for Python 3.7, which was created back in 2016.

What’s new in 3.7? Why should you upgrade? Is there anything new that’s actually useful? I’ll answer these questions for you by walking through some examples of the new features. Whilst there’s not much in this release that will make a difference to the Python beginner, there’s plenty of small changes for seasoned coders and a few headline features you’ll want to know about.

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Car Revival According to Tesla

Frankencars are built from the parts of several cars to make one usable vehicle. [Jim Belosic] has crossed the (finish) line with his Teslonda. In the most basic sense, it is the body of a Honda Accord on top of the drive train of a Tesla Model S. The 1981 Honda was the make and model of his first car, but it wasn’t getting driven. Rather than sell it, he decided to give it a new life with electricity, just like Victor Frankenstein.

In accord with Frankenstein’s monster, this car has unbelievable strength. [Jim] estimates the horsepower increases by a factor of ten over the gas engine. The California-emissions original generates between forty and fifty horsepower while his best guess places the horsepower over five-hundred. At this point, the Honda body is just holding on for dear life. Once all the safety items, like seatbelts, are installed, the driver and passengers will be holding on for the same reason.

This kind of build excites us because it takes something old, and something modern, and marries the two to make something in a class of its own. And we hate to see usable parts sitting idle.

Without a body, this electric car scoots around with its driver all day, and this Honda doesn’t even need the driver inside.

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Optical Tach Addresses the Need for Spindle Speed Control

With CNC machines, getting the best results depends on knowing how fast your tool is moving relative to the workpiece. But entry-level CNC routers don’t often include a spindle tachometer, forcing the operator to basically guess at the speed. This DIY optical spindle tach aims to fix that, and has a few nice construction tips to boot.

The CNC router in question is the popular Sienci, and the 3D-printed brackets for the photodiode and LED are somewhat specific for that machine. But [tmbarbour] has included STL files in his exhaustively detailed write-up, so modifying them to fit another machine should be easy. The sensor hangs down just far enough to watch a reflector on one of the flats of the collet nut; we’d worry about the reflector surviving tool changes, but it’s just a piece of shiny tape that’s easily replaced.  The sensor feeds into a DIO pin on a Nano, and a small OLED display shows a digital readout along with an analog gauge. The display update speed is decent — not too laggy. Impressive build overall, and we like the idea of using a piece of PLA filament as a rivet to hold the diodes into the sensor arm.

Want to measure machine speed but don’t have a 3D printer? No worries — a 2D-printed color-shifting tach can work too.

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Measuring Gait Speed Passively to Diagnose Diseases

You may not realize it, but how fast a person walks is an important indicator of overall health. We all instinctively know that we lag noticeably when a cold or the flu hits, but monitoring gait speed can help diagnose a plethora of chronic diseases and conditions. Wearables like Fitbit would be one way to monitor gait speed, but the Computer Science and Artificial Intelligence Lab at MIT thinks there’s a better way:  a wireless appliance that measures gait speed passively.

CSAIL’s sensor, dubbed WiTrack (PDF), is a wall-mounted plaque that could be easily concealed as a picture or mirror. It sends out low-power RF signals between about 5- and 7-GHz to perform 3D motion tracking in real time. The WiTrack sensor has a resolution of about 8 cm at those frequencies. With their WiGait algorithms (PDF), the CSAIL team led by [Chen-Yu Hsu] is able to measure not only overall walking speed, but also stride length. That turns out to be critical to predicting the onset of such diseases as Parkinson’s, which has a very characteristic shuffling gait in the early phase of the disease. Mobility impairments from other diseases, like ALS and multiple sclerosis, could also be identified.

WiTrack builds on [Hsu]’s previous work with through-wall RF tracking. It’s nice to see a novel technique coming closer to a useful product, and we’ll be watching to see where this one goes.

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The Right Circuit Turns Doppler Module into a Sensor

Can you buy a working radar module for $12? As it turns out, you can. But can you make it output useful information? According to [Mathieu], the answer is also yes, but only if you ignore the datasheet circuit and build this amplification circuit for your dirt cheap Doppler module.

The module in question is a CDM324 24-GHz board that’s currently listing for $12 on Amazon. It’s the K-band cousin of the X-band HB100 used by [Mathieu] in a project we covered a few years back, but thanks to the shorter wavelength the module is much smaller — just an inch square. [Mathieu] discovered that the new module suffered from the same misleading amplifier circuit in the datasheet. After making some adjustments, a two-stage amp was designed and executed on a board that piggybacks on the module with a 3D-printed bracket.

Frequency output is proportional to the velocity of the detected object; the maximum speed for the sensor is only 14.5 mph (22.7 km/h), so don’t expect to be tracking anything too fast. Nevertheless, this could be a handy sensor, and it’s definitely a solid lesson in design. Still, if your tastes run more toward using this module on the 1.25-cm ham band, have a look at this HB100-based 3-cm band radio.

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