Does Getting Into Your Garage Really Need To Be Difficult?

Probably the last thing anyone wants when coming home from a long day at work or a trip is to be hassled at the last possible moment — gaining entrance to your house. But for some home automation enthusiasts, that’s just what happened when they suddenly learned that their own garage doors had betrayed them.

The story basically boils down to this: Chamberlain, a US company that commands 60% of the garage door market, recently decided to prevent “unauthorized usage” of their MyQ ecosystem through third-party apps. Once Chamberlain rolled out the change, users of Home Assistant and other unauthorized apps found themselves unable to open or close their doors with the apps they were accustomed to.

Those of us with custom smart home setups can relate to how frustrating it is when something disturbs the systems you’ve spent a lot of time tweaking and optimizing. It’s especially upsetting for users who both Chamberlain hardware specifically because it was supported by Home Assistant, only to have the company decide to drop support. This feels like false advertising, but we strongly suspect that buried in the EULA users must have agreed to at some point is a clause that essentially says, “We can do anything we want and tough noogies to you.” And if you read through the article linked above, you’ll get an idea why Chamberlain did this — they probably didn’t like the idea that users were avoiding their ad-spangled MyQ app for third-party interfaces, depriving them of ad revenue and the opportunity for up-selling.

We feel the frustration of these users, but rather than curse the darkness, perhaps this will light a candle of righteous rage that leads to a clever workaround. The Home Assistant blog article mentions a dongle called ratgdo, which should allow any door with plain old dry contacts to work via MQTT or ESPHome. It’s extra work that users shouldn’t have to put in, but maybe getting one over on The Man would be worth the effort.

Thanks to [KC] for the tip; please keep us posted on your workaround.

3D Printing Improves Passive Pixel Water Gauge

Here at Hackaday, we feature all kinds of projects, and we love them all the same. But some projects are a little easier to love than others, especially those that get the job done in as simple a way as possible, with nothing extra to get in the way. This completely electronics-free water gauge is a great example of doing exactly as much as needs to get done, and not a bit more.

If this project looks a bit familiar, it’s because we featured [Johan]’s previous version of “Pixel Pole” a few years back. Then as now, the goal of the build is to provide a highly visible level gauge for a large water tank that’s part of an irrigation system. The basic idea was to provide a way of switching a pump on when the tank needed filling, and off when full. [Johan] accomplished this with a magnetic float inside the tank and reed switches at the proper levels outside the tank, and then placed a series of magnetic flip dots along the path of the float to provide a visual gauge of the water level. The whole thing was pretty clever and worked well enough.

But the old metal flip dots were getting corroded, so improvements were in order. The new flip dots are 3D printed, high-visibility green on one side and black on the other. The only metal parts are the neodymium magnet pressed into a slot in the disc and a sewing pin for the axle. The housing for each flip dot is also printed, with each module snapping to the next so you can create displays of arbitrary height. The video below shows printing, assembly, and the display in action.

[Johan]’s improvements are pretty significant, especially in assembly; spot-welding was a pretty cool method to use in the first version, but printing and snapping parts together scales a lot better. And this version seems like it’ll be much happier out in the elements too. Continue reading “3D Printing Improves Passive Pixel Water Gauge”

Brick-Laying Machine Builds Without Mortar

Move over, 3D printed houses. There’s a new game in town, and it is able to use standard concrete blocks to build the walls of a house in just one day.

Australian company FBR’s Hadrian X is a tablet-controlled system that follows CAD models to lay the blocks one by one. As you can see in the video after the break, the blocks are laid so quickly that there’s no time for mortar, so they dip the bottom of each block in construction adhesive instead. In the second video after the break, you can watch Hadrian-X build a curved wall.

There are several things to consider when it comes to outdoor robots, such as wind and unwanted vibration. In order to correct for these nuisances, FBR came up with Dynamic Stabilisation Technology (DST). While we don’t have a lot of details on DST, the company calls it “a highly accurate system that continuously adjusts the position of a robot’s end effector to ensure it is always held with stability at the correct point in 3D space.”

Curious about printed housing? Here’s the current-ish state of affairs.

Continue reading “Brick-Laying Machine Builds Without Mortar”

Keeping Badgers At Bay With Tensorflow

Human-animal conflict is always a contentious issue, and finding ways to prevent damage without causing harm to the animals often requires creative solutions. [James Milward] needed a humane method to stop badgers and foxes from uprooting his garden, leading him to create the Furbinator 3000, a system that combines computer vision with audio deterrents..

[James] initially tried using scent repellents (which were ignored) and blocking access to his garden (resulting in more digging), but found some success with commercial ultrasonic audio repellent devices. However, these had to be manually turned off during the day to avoid annoying activation of the PIR motion sensors by [James] and his family, and the integrated solar panels couldn’t keep up with the load.

This presented a good opportunity to try his hand at practical machine vision. He already had a substantial number of sample images from the Ring cameras in his garden, which he turned into a functional TensorFlow Lite model with about 2.5 hours of training. He linked it with event-activated RTSP streams from his Ring cameras using the ring-mqtt library. To minimize false positives on stationary objects, he incorporated a motion filter into the processing pipeline. When it identifies a fox or badger with reasonable accuracy, it generates an MQTT event.

[James] modified the ultrasonic devices so they would react to these events using an ESP8266-based WeMos D1 Mini Pro development board and added an external 5 V power supply for sustained operation. All development was performed in a Docker container which simplified deployment on a Raspberry Pi 4.

After implementing the system, [James] woke up to the satisfying sight of his garden remaining untouched overnight, a victory that even earned him some coverage by the BBC.

Thanks for the tip [Laurent]!

Autonomous Wheelchair Lets Jetson Do The Driving

Compared to their manual counterparts, electric wheelchairs are far less demanding to operate, as the user doesn’t need to have upper body strength normally required to turn the wheels. But even a motorized wheelchair needs some kind of input from the user to control it, which still may pose a considerable challenge depending on the individual’s specific abilities.

Hoping to improve on the situation, [Kabilan KB] has developed a self-driving electric wheelchair that can navigate around obstacles by feeding the output of an Intel RealSense Depth Camera and LiDAR module into a Jetson Nano Developer Kit running OpenCV. To control the actual motors, the Jetson is connected to an Arduino which in turn is wired into a common L298N motor driver board.

As [Kabilan] explains on the NVIDIA Blog, he specifically chose off-the-shelf components and the most affordable electric wheelchair he could find to bring the total cost of the project as low as possible. An undergraduate from the Karunya Institute of Technology and Sciences in Coimbatore, India, he notes that this sort of assistive technology is usually only available to more affluent patients. With his cost-saving measures, he hopes to address that imbalance.

While automatic obstacle avoidance would already be a big help for many users, [Kabilan] imagines improved software taking things a step further. For example, a user could simply press a button to indicate which room of the house they want to move to, and the chair could drive itself there automatically. With increasingly powerful single-board computers and the state of open source self-driving technology steadily improving, it’s not hard to imagine a future where this kind of technology is commonplace.

A hot tub with a smartphone in front showing real-time sensor data

ESP32 Keeps Track Of Hot Tub’s Vital Signs

Like swimming pools, hot tubs need regular monitoring to ensure their water stays clean and clear. An average person might take a water quality reading once or twice a week using test strips, but such a low sampling rate obviously won’t do for a hacker. [Stephen Carey] has therefore built a hot tub monitor that checks the water quality every minute and reports it on a neat mobile dashboard.

[Stephen]’s system uses commercially available sensors that track pH levels and Oxidation-Reduction Potential (ORP), both basic measurements that indicate water quality. A second set of sensors keeps track of the temperature of the water and the outside air, which should help in finding insulation failures and keeping energy use under control.

A set of graphs showing a hot tub's pH and ORP over time, with a significant spike in both near the beginningAn ESP32 reads the sensors and sends out the data through WiFi. [Stephen] programmed the ESP32 in MicroPython, using an MQTT driver to connect it to Home Assistant. By looking at the graphs generated, you can tell when someone entered the tub from a step change in pH and ORP. It’s even possible to generate alerts when any of the values drift outside their acceptable range – we can already imagine an alarm going off when someone enters without having showered first.

The system also has a calibration mode to check the sensors against a well-defined buffer solution. As with many chemical sensors, the pH and ORP probes gradually lose their active material and need to be replaced after about a year. Good ones aren’t cheap, but [Stephen] has found pretty decent low-cost alternatives on AliExpress that should be fine for a home setup.

If you also want your tub or pool to be actively managed, you’ll need a more complex system, perhaps even one that can also dispense chemicals. If your hot tub is heated by a wood fire, however, all you need is a way to alert the person tending the fire.

Open Source Tracker Keeps An Eye On Furry Friends

Most of the time, you’ll know where your cats are — asleep on the bed about 23.5 hours a day and eating or pooping the rest of the time. But some cats are more active than others, so there’s commercial options for those who want to keep tabs on their pet. Unfortunately, [Sahas Chitlange] didn’t like any of them, so he designed and built his own open source version: FindMyCat.io.

The system is in two parts: a module that fits onto a cat collar, and a home station that, well, stays at home. It offers a variety of tracking modes. In home mode, the home station signals the collar every 10 seconds, which stays in a deep sleep most of the time. If the collar doesn’t get a signal from the home station, it switches to ping mode, where it will wait for a signal from the FindMyCat over the LTE-M connection and report its location.

Finally, the app can set the collar to Lost Kitteh mode, where the collar will send a location to the app every seven minutes or thirty seconds. The collar also supports a direction-finding feature, using the ultra wideband (UWB) feature of recent Apple iPhones to point you in the direction and distance of the tracked cat.

The collar is built around a Nordic Semiconductor NRF-9160, a System in a Package (SiP) that does most of the heavy lifting as it includes GPS, an LTE-M modem, and an ARM processor. One interesting feature here: [Sahas] doesn’t make his antennas on the PCB, but instead uses an Ignion NN03-310, an off-the-shelf antenna that is already qualified for LTE-M use. That means this system can be connected to almost any LTE-M network without getting yelled at for using unqualified hardware and making the local cell towers explode.

The collar also includes a DWM3001CDK ultrawideband (UWB) module used for the locator feature. The accompanying app uses this and Apple’s UWB support to show the user which direction the cat is in, and how far away it is. The app isn’t in the Apple App Store yet, so you’ll need to sign up for an Apple Developer account to use it. We’d love to hear from anyone who takes it for a test drive with their own pet.

Continue reading “Open Source Tracker Keeps An Eye On Furry Friends”