36C3: Phyphox – Using Smartphone Sensors For Physics Experiments

It’s no secret that the average smart phone today packs an abundance of gadgets fitting in your pocket, which could have easily filled a car trunk a few decades ago. We like to think about video cameras, music playing equipment, and maybe even telephones here, but let’s not ignore the amount of measurement equipment we also carry around in form of tiny sensors nowadays. How to use those sensors for educational purposes to teach physics is presented in [Sebastian Staacks]’ talk at 36C3 about the phyphox mobile lab app.

While accessing a mobile device’s sensor data is usually quite straightforwardly done through some API calls, the phyphox app is not only a shortcut to nicely graph all the available sensor data on the screen, it also exports the data for additional visualization and processing later on. An accompanying experiment editor allows to define custom experiments from data capture to analysis that are stored in an XML-based file format and possible to share through QR codes.

Aside from demonstrating the app itself, if you ever wondered how sensors like the accelerometer, magnetometer, or barometric pressure sensor inside your phone actually work, and which one of them you can use to detect toilet flushing on an airplane and measure elevator velocity, and how to verify your HDD spins correctly, you will enjoy the talk. If you just want a good base for playing around with sensor data yourself, it’s all open source and available on GitHub for both Android and iOS.

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Flux Gate Magnetometers Make A Special Current Probe

There are moments when current measurement is required on conductors that can’t be broken to insert a series resistor, nor encircled with a current transformer. These measurements require a completely non-invasive technique, and to satisfy that demand there are commercial magnetometer current probes. These probes are however not for the light of wallet, so [ensgoldmine] has created a much cheaper alternative.

The Texas Instruments GRV425 flux gate magnetometer integrated circuit on its TI evaluation module provides the  measuring element placed at the tip of a probe as close as possible to the conductor to be measured, with another GRV425 module at the head of the probe to measure ambient magnetic field for calibration purposes.  An Arduino Due measures and processes the readings, chosen due to its higher-resolution ADC than the more ubiquitous Arduino Uno.

The write-up is interesting even if you have no need for a current probe, because of its introduction to these sensing elements. Because it’s a rare first for Hackaday, we’ve never taken a close look at them before other than as an aside when talking about a scientific instrument on Mars.

Detecting Cars With An ESP8266 Magnetometer

Having a motorized gate on your driveway is great, but only if there’s an easy way to trigger it. [Andrew] says the gate at his parent’s place could only be controlled by manually pushing a button on the panel or with a dinky remote that didn’t have nearly the range they wanted. So he decided to build his own magnetometer allowing the gate to automatically open when a car was trying to leave.

Naturally, there are commercial offerings that would solve this problem. But with a sticker price of more than $150 USD, [Andrew] was more than happy to spend a bit of time tinkering to get the job done for less than 1/10th the cost with an ESP8266 and a QMC5883X series magneto-resistive sensor. Of course, this is one of those projects that seems simple enough in your head, but ends up taking a bit of finesse to pull off in the real-world.

For one, [Andrew] had to figure out how to prevent false positives. Pretty much any object brought close enough to the sensor, including his hand, would cause it to react. He ended up coming up with a way to use a rolling average to prevent the gate from firing off just because a squirrel ran past. The built-in safeties are designed to ensure that the gate only opens when an actual car is sitting in the appropriate spot for long enough.

Speaking of, we love how [Andrew] deployed the QMC5883X sensor for this project. The small sensor board and a few moisture-absorbing packets were placed in a Sonoff IP66 waterproof enclosure, and buried under the rocks of the driveway. A standard CAT5 cable is used to tether it to the ESP8266, relay, and assorted other goodies that now live in the gate’s control box. In the future he says the cable will likely have to go into a conduit, but for now the system is working more or less how he expected.

If your estate isn’t quite palatial enough to have a motorized gate out front, we’ve seen plenty of projects that add some much-needed intelligence to the humble garage door opener which might be more your speed.

Test Ideas Now With Sensors Already In Your Pocket

When project inspiration strikes, we’d love to do some quick tests immediately to investigate feasibility. Sadly we’re usually far from our workbench and its collection of sensor modules. This is especially frustrating when the desired sensor is in the smartphone we’re holding, standing near whatever triggered the inspiration. We could download a compass app, or a bubble level app, or something similar to glimpse sensor activity. But if we’re going to download an app, consider Google’s Science Journal app.

It was designed to be an educational resource, turning a smartphone’s sensor array into a pocket laboratory instrument and notebook for students. Fortunately it will work just as well for makers experimenting with project ideas. The exact list of sensors will depend on the specific iOS/Android device, but we can select a sensor and see its output graphed in real-time. This graph can also be recorded into the journal for later analysis.

Science Journal was recently given a promotional push by the band OK Go, as part of their OK Go Sandbox project encouraging students to explore, experiment, and learn. This is right up the alley for OK Go, who has a track record of making music videos that score high on maker appeal. Fans would enjoy their videos explaining behind-the-scene details in the context of math, science, and music.

An interesting side note. Anyone who’s been to Hackaday Superconference or one of the monthly Hackaday LA meetups will likely recognized the venue used in many of the OK Go Sandbox videos. Many of them were filmed at the Supplyframe Design Lab in Pasadena. It’s also nice to see AnnMarie Thomas (Hackaday Prize Judge from 2016 and 2017) collaborated with OK Go for the Sandbox project.

While the Science Journal app has provisions for add-on external sensors, carrying them around would reduce its handy always-available appeal. Not that we’re against pairing smartphones with clever accessories to boost their sensing capabilities: we love them! From trying to turn a smartphone into a Tricorder, to an inexpensive microscope, to exploring serious medical diagnosis, our pocket computers can do it all.

[via Engadget]

 

Tell Time With A Reverse-Sundial Watch

[Xose Pérez] set out to make a sundial wristwatch by combining a magnetometer a small nylon bolt for the gnomon, but it doesn’t work like you’d think. Instead of using the magnetometer to point the sundial north, you angle the watch until the bolt’s shadow matches the white line on the PCB, and the ATmega328P computes the azimuth of the sun and determines the time thereby. To display the time he used one of those QDSP-6064 bubble displays, because sundials are retro.

His description of the project build includes a lot of fun anecdotes, like him attempting to solder the LCC connections of the HMC5883 magnetometer before giving up and making use of Seeedstudio’s PCBA service. He got 10 boards back with the ATmega and magnetometer populated while leaving the rest for [Xose] to fill in.

One fun detail of the project? You can’t tell what time it is without the sun, but you can’t read the bubble display in bright sunlight.

If you’re looking for more watch projects we’ve published, check out this wrist-controlled watch, the Chronio DIY watch, and this cool nixie-tube watch.

Sense All The Things With A Synthetic Sensor

What will it take to make your house smarter than you? Judging from the price of smart appliances we see in the home centers these days, it’ll take buckets of cash. But what if you could make your home smarter — or at least more observant — with a few cheap, general purpose “supersensors” that watch your every move?

Sounds creepy, right? That’s what [Gierad Laput] and his team at the Carnegie Mellon Human-Computer Interaction Institute thought when they designed their broadband “synthetic sensor,” and it’s why they purposely omitted a camera from their design. But just about every other sensor under the sun is on the tiny board: an IR array, visible light sensors, a magnetometer, temperature, humidity, and pressure sensors, a microphone, PIR, and even an EMI detector. Of course there’s also a WiFi module, but it appears that it’s only for connectivity and not used for sensing, although it clearly could be. All the raw data is synthesized into a total picture of the goings on in within the platform’s range using a combination of machine learning and user training.

The video after the break shows the sensor detecting typical household events from a central location. It’s a powerful idea and we look forward to seeing how it moves from prototype to product. And if the astute reader recognizes [Gierad]’s name, it might be from his past appearance on these pages for 3D-printed hair.

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Your Arm Is The Ideal Controller

With interest and accessibility to both wearable tech and virtual reality approaching an all-time high, three students from Cornell University — [Daryl Sew, Emma Wang, and Zachary Zimmerman] — seek to turn your body into the perfect controller.

That is the end goal, at least. Their prototype consists of three Kionix tri-axis accelerometer, gyroscope and magnetometer sensors (at the hand, elbow, and shoulder) to trace the arm’s movement. Relying on a PC to do most of the computational heavy lifting, a PIC32 in a t-shirt canister — hey, it’s a prototype! — receives data from the three joint positions, transmitting them to said PC via serial, which renders a useable 3D model in a virtual environment. After a brief calibration, the setup tracks the arm movement with only a little drift in readings over a few minutes.

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