Cat Litter Tray Joins The Internet Of Things

August 28, 2019 by Lewin Day 25 Comments

Keeping a cat as a pet can be rewarding, but it’s always important to consider how to handle the mess – and we’re not just talking about the tea cups pushed off tables here. To handle just this task, [Igor] decided to hook his cat litter box up to the internet of things.

Monitoring the litter box brings several useful advantages. Load cells enable the weight of the litter tray to be monitored, allowing sand levels and the weight of the cats to be checked at regular intervals. Additionally, a door sensor keeps a record of comings and goings, giving an idea of how frequently the box has been used, and whether or not it may be time for cleaning. It’s all powered by an ESP32, hooked up to the Thingspeak platform. This allows for easy graphing and analysis of the data collected from the system. The electronics is then neatly installed in an attractive two-tone 3D printed enclosure with a pleasing cat motif.

It’s a great example of using some cheap off-the-shelf parts to ease the regular tasks of daily life. Building your own gear can be beneficial too, especially when Big Litter implements DRM on their hardware.

Inventor And Detective Create Range Of Snack-Hiding Devices

August 25, 2019 by Maya Posch 8 Comments

Anyone who has had to deal with siblings, their friends, flatmates or parents who are overly fond of snacks may know this issue: you bought some snacks for your own consumption, but before you can get to them they have vanished. Naturally, nobody knows what happened to said snacks and obviously outraged that anyone would dare to do such a dastardly thing like eating someone else’s snacks.

This is the premise behind British inventor [Colin Furze]’s new series of YouTube videos (embedded after the break). Teaming up with former Scotland Yard detective [Peter Bleksley], their goal is to find ways to hide snacks around the house where curious and peckish individuals will not find them. Though a snack-company sponsored series (Walkers) and featuring snack names that will ring no bells for anyone outside of the UK, it nevertheless shows some innovative ways to hide snacks.

The first episode shows how one can hide snacks (or something else, naturally) inside a door. The second tweaks a standing lamp to add some hidden drawers, and the third episode creates a hidden compartment behind a television. Perhaps the most intriguing part of these episodes is the way it highlights how easy it is to not just hide snacks around the house, but also devices for automation and monitoring. Just think how one could use these tricks for IoT projects and the like.

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The Danish Internet Of Hot Tubs

August 24, 2019 by Jenny List 2 Comments

Every hacker camp has its own flavor, and BornHack 2019 in the Danish countryside gave us the opportunity to sample some hacker relaxation, Scandinavian style. Among the attractions was a wood-fired hot tub of gargantuan proportions, in which the tired attendee could rejuvenate themselves at 40 Celcius in the middle of the forest. A wood-fired hot tub is not the easiest of appliances to control, so to tame it [richard42graham] and a group of Danish hackerspace friends took it upon themselves to give it an internet-connected temperature sensor.

The starting point was a TMP112 temperature sensor and an ESP8266 module, which initially exposed the temperature reading via a web interface, but then collapsed under too much load. The solution was to make the raw data available via MQTT, and from that create a web interface for the event bar, Twitter and IRC bots. There was even an interface to display hot tub temperature on the ubiquitous OHMlights dotted around the camp.

It’s more normal to control a hot tub via an electric heater, but since the wood fire on this one has to be tended by a camp volunteer it made sense to use the IRC system as an alert. It will be back at BornHack 2020, so we’ll have to do our job here at Hackaday and spend a long time lounging in the hot tub in the name of journalistic research to see how well it works.

Exploring The Science Behind Dirty Air Filters

August 18, 2019 by Tom Nardi 34 Comments

Obviously, if the air filters in your home HVAC system are dirty, you should change them. But exactly how dirty is dirty? [Tim Rightnour] had heard it said that if you didn’t change your filter every month or so, it could have a detrimental effect on the system’s energy consumption. Thinking that sounded suspiciously like a rumor Big Filter™ would spread to bump up their sales, he decided to collect his own data and see if there was any truth to it.

There’s a number of ways you could tackle a project like this, but [Tim] wanted to keep it relatively simple. A pressure sensor on either side of the filter should tell him how much it’s restricting the airflow, and recording the wattage of the ventilation fan would give him an idea on roughly how hard the system was working.

Now [Tim] could have got this all set up and ran it for a couple months to see the values gradually change…but who’s got time for all that? Instead, he recorded data while he switched between a clean filter, a mildly dirty one, and one that should have been taken out back and shot. Each one got 10 minutes in the system to make its impression on the sensors, including a run with no filter at all to serve as a baseline.

The findings were somewhat surprising. While there was a sizable drop in airflow when the dirty filter was installed, [Tim] found the difference between the clean filter and mildly soiled filter was almost negligible. This would seem to indicate that there’s little value in preemptively changing your filter. Counter-intuitively, he also found that the energy consumption of the ventilation fan actually dropped by nearly 50 watts when the dirty filter was installed. So much for a clean filter keeping your energy bill lower.

With today’s cheap sensors and virtually infinite storage space to hold the data from them, we’re seeing hackers find all kinds of interesting trends in everyday life. While we don’t think your air filters are spying on you, we can’t say the same for those fancy new water meters.

Home Automation At A Glance Using AI Glasses

August 15, 2019 by Tom Nardi 3 Comments

There was a time when you had to get up from the couch to change the channel on your TV. But then came the remote control, which saved us from having to move our legs. Later still we got electronic assistants from the likes of Amazon and Google which allowed us to command our home electronics with nothing more than our voice, so now we don’t even have to pick up the remote. Ushering in the next era of consumer gelification, [Nick Bild] has created ShAIdes: a pair of AI-enabled glasses that allow you to control devices by looking at them.

Of course on a more serious note, vision-based home automation could be a hugely beneficial assistive technology for those with limited mobility. By simply looking at the device you want to control and waving in its direction, the system knows which appliance to activate. In the video after the break, you can see [Nick] control lamps and his speakers with such ease that it almost looks like magic; a defining trait of any sufficiently advanced technology.

So how does it work? A Raspberry Pi camera module mounted to a pair of sunglasses captures video which is sent down to a NVIDIA Jetson Nano. Here, two separate image classification Convolutional Neural Network (CNN) models are being used to identify objects which can be controlled in the background, and hand gestures in the foreground. When there’s a match for both, the system can fire off the appropriate signal to turn the device on or off. Between the Nano, the camera, and the battery pack to make it all mobile, [Nick] says the hardware cost about $150 to put together.

But really, the hardware is only one small piece of the puzzle in a project like this. Which is why we’re happy to see [Nick] go into such detail about how the software functions, and crucially, how he trained the system. Just the gesture recognition subroutine alone went through nearly 20K images so it could reliably detect an arm extended into the frame.

If controlling your home with a glance and wave isn’t quite mystical enough, you could always add an infrared wand to the mix for that authentic Harry Potter experience.

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Uncovering The Echo Dot’s Hidden USB Port

August 15, 2019 by Tom Nardi 62 Comments

If you upgraded to Amazon’s latest Echo Dot, you might have been surprised to find that the diminutive voice assistant had shed its USB port. Earlier models of the Dot used a garden variety micro USB port for power, which hackers eventually figured out also provided a helpful way to snoop around inside the device’s firmware. The fact that the USB port was deleted on the latest Echo Dot in favor of a simple barrel connector for power was seen by some as a sign that Amazon was trying to keep curious owners out of their hardware.

But as [Brian Dorey] shows, all they did was put a bump in the road. While they removed the external USB connector, the traces for it are still on the board waiting to be accessed. Even better, it turns out the USB data lines are connected to the test points located on the bottom of the Dot. All you need is a simple breakout that will connect through the existing opening in the device’s case, and you’ve got your USB port back.

So what can you do with USB on the Echo Dot? Well, not much right now. [Brian] found that the Dot shows up as a Mediatek device under Linux using lsusb, and fastboot can see it and even confirms the presence of a locked bootloader. It’s going to take some work from the community to see how deep this particular rabbit hole goes.

Even if you’re not interested in restoring its USB port, [Brian] has uncovered a wealth of fascinating hardware information about the Echo Dot during his deep-dive. He’s mapped out many of the test points located throughout the device’s PCBs, and found a few interesting points that might be worth further investigation. For example, he found that driving one of the pins high would trigger the Dot to mute its microphones; which could be useful for anyone looking to cover Alexa’s ears.

[Brian] first cracked open the Echo Dot last month, after scoring one for cheap during Amazon’s Prime Day sale. It looks like he’s making fairly rapid progress on unraveling the mysteries of this popular gadget, and we’re very interested in seeing where this research takes us.

Data Mining Home Water Usage; Your Water Meter Knows You A Bit Too Well

August 14, 2019 by Tom Nardi 70 Comments

The average person has become depressingly comfortable with the surveillance dystopia we live in. For better or for worse, they’ve come to accept the fact that data about their lives is constantly being collected and analyzed. We’re at the point where a sizable chunk of people believe their smartphone is listening in on their personal conversations and tailoring advertisements to overheard keywords, yet it’s unlikely they’re troubled enough by the idea that they’d actually turn off the phone.

But even the most privacy-conscious among us probably wouldn’t consider our water usage to be any great secret. After all, what could anyone possibly learn from studying how much water you use? Well, as [Jason Bowling] has proven with his fascinating water-meter data research, it turns out you can learn a whole hell of a lot by watching water use patterns. By polling a whole-house water flow meter every second and running the resulting data through various machine learning algorithms, [Jason] found there is a lot of personal information hidden in this seemingly innocuous data stream.

The key is that every water-consuming device in your home has a discernible “fingerprint” that, with enough time, can be identified and tracked. Appliances that always use the same amount of water, like an ice maker or dishwasher, are obvious spikes among the noise. But [Jason] was able to pick up even more subtle differences, such as which individual toilet in the home had been flushed and when.

Further, if you watch the data long enough, you can even start to identify information about individuals within the home. Want to know how many kids are in the family? Monitoring for frequent baths that don’t fill the tub all the way would be a good start. Want to know how restful somebody’s sleep was? A count of how many times the toilet was flushed overnight could give you an idea.

In terms of the privacy implications of what [Jason] has discovered, we’re mildly horrified. Especially since we’ve already seen how utility meters can be sniffed with nothing more exotic than an RTL-SDR. But on the other hand, his write-up is a fantastic look at how you can put machine learning to work in even the most unlikely of applications. The information he’s collected on using Python to classify time series data and create visualizations will undoubtedly be of interest to anyone who’s got a big data problem they’re looking to solve.