One of the most power-hungry devices in our homes, besides the air conditioner or heater, is our refrigerator and freezer. It’s especially so if the door doesn’t close all the way or the magnetic seal doesn’t seat properly. [Javier] took to solving a recurring problem with his personal fridge by attaching an alarm to the door to make sure that it doesn’t consume any more power than it absolutely needs.
At its core the device is straightforward. A micro switch powers a small microcontroller only when the door is open. If the door is open for too long, the microcontroller swings into action. The device then powers up a small wireless card (which looks like a variant of the very well-documented ESP module), that communicates with his microwave of all things, which in turn alerts him with an audible, spoken alarm that the refrigerator hasn’t closed all the way. It’s all powered with a battery that will eventually need to be recharged.
While there are certainly easier ways to implement an alarm, the use of the spoken alarm is a nice touch for this project, and the power savings that can be realized are not insignificant. There’s also the added benefit that [Javier] can prevent his freezer from frosting over. If you’re in the mood for other great fridge hacks, there are other exciting, novel, and surely one-of-a-kind ways to trick out your refrigerator.
Continue reading “Fridge Alarm Speaks, and Saves Power & Food”
[Martin Rowe] over at EDN recently put a $200 wireless oscilloscope to the test. The Aeroscope 100A is a single channel scope in a probe body that communicates back to an Apple smartphone or tablet via Bluetooth LE. You can see the video from the post, below.
The original prototype of the device had a high bandwidth, but the production model only manages to have a 20 MHz bandwidth at 100 megasamples per second: nothing earth-shattering.
Continue reading “Wireless Oscilloscope Review”
To a ham radio operator used to “short”-wave antennas with lengths listed in tens of meters, the tiny antennas used in the gigahertz bands barely even register. But if your goal is making radio electronics that’s small enough to swallow, an antenna of a few centimeters is too big. Physics determines plausible antenna sizes, and there’s no way around that, but a large group of researchers and engineers have found a way of side-stepping the problem: resonating a nano-antenna acoustically instead of electromagnetically.
Normal antennas are tuned to some extent to the frequency that you want to pick up. Since the wavelength of a 2.5 GHz electromagnetic wave in free space is 120
cm mm, most practical antennas need a wire in the 12-60 cm mm range to bounce signals back and forth. The trick in the paper is to use a special piezomagnetic material as the antenna. Incoming radio waves get quickly turned into acoustic waves — physical movement in the nano-crystals. Since these sound waves travel a lot slower than the speed of light, they resonate off the walls of the crystal over a much shorter distance. A piezoelectric film layer turns these vibrations back into electrical signals.
Ceramic chip antennas use a similar trick. There, electromagnetic waves are slowed down inside the high-permittivity ceramic. But chip antennas are just slowing down EM waves, whereas the research demonstrated here is converting the EM to sound waves, which travel many orders of magnitude slower. Nice trick.
Granted, significant material science derring-do makes this possible, and you’re not going to be fabricating your own nanoscale piezomagnetic antennas any time soon, but with everything but the antenna getting nano-ified, it’s exciting to think of a future where the antennas can be baked directly into the IC.
Thanks [Ostracus] for the tip in the comments of this post on antenna basics. Via [Science Magazine].
Many of us will have at some time over the last couple of years bought a LoRaWAN module or two to evaluate the low power freely accessible wireless networking technology. Some have produced exciting and innovative projects using them while maybe the rest of us still have them on our benches as reminders of projects half-completed.
If your LoRaWAN deployment made it on-air, you’ll be familiar with the range that can be expected. A mile or two with little omnidirectional antennas if you are lucky. A few more miles if you reach for something with a bit of directionality. Add some elevation, and range increases.
A couple of weeks ago at an alternative society festival in the Netherlands, a balloon was launched with a LoRaWAN payload on board that was later found to have made what is believed to be a new distance record for successful reception of a LoRaWAN packet. While the balloon was at an altitude of 38.772 km (about 127204.7 feet) somewhere close to the border between Germany and the Netherlands, it was spotted by a The Things Network node in Wroclaw, Poland, at a distance of 702.676km, or about 436 miles. The Things Network is an open source, community driven effort that has built a worldwide LoRaWAN network.
Of course, a free-space distance record for a balloon near the edge of space might sound very cool and all that, but it’s not going to be of much relevance when you are wrestling with the challenge of getting sensor data through suburbia. But it does provide an interesting demonstration of the capabilities of LoRaWAN over some other similar technologies, if a 25mW (14dBm) transmitter can successfully send a packet over that distance then perhaps it might be your best choice in the urban jungle.
If you’re curious about LoRaWAN, you might want to start closer to home and sniff for local activity.
Many years ago, in a rainy concrete jungle on the west coast of Australia, I worked for a medium-sized enterprise doing a variety of office-based tasks. Somehow, I found myself caught up in planning a product launch event outside the official remit of my position. We got through it, but not before the audiovisual (AV) setup of the event turned into one giant hack.
The initial planning stages went remarkably smoothly until less than a month out from the big day when three weeks of frantic changes and revisions to the presentation rained down. These were some of the hardest days of my working life to date, as it seemed that we would lock in a new arrangement, only to tear it up days later as some new vital criteria came to light, throwing everything back into disarray.
Things came to a head on the night before the event. Working with two different AV teams we had planned for four projection screens and five flat screen televisions spread throughout the venue and controlled from the central AV desk. But somewhere in all those changes the televisions were set up to all display a still image, or nothing at all. I needed to show different videos on each and have the ability to black them all out.
It was at this point I realized we were screwed. The production team simply didn’t have the hardware to drive another five screens, but they could source it — for the sum of $5000. Management were furious, and were under the impression, like myself that this was what we had asked and paid for already. I was at an impasse, and beginning to wonder if I’d have a job come Monday. I wandered off to a corner to curse, and more importantly, think. After all, I’m a hacker — I can get through this.
Continue reading “Hacker Heroism: Building Your Way Out of AV Hell”
What to do once you have a sprinkler system installed on your property: buy a sprinkler control system or make your own? The latter, obviously.
[danaman] was determined to hack together a cheap, IoT-enabled system but it wasn’t easy — taking the better part of a year to get working. Instead of starting right from scratch, he used the open-source Sustainable Irrigation Platform(SIP) control software — a Python sprinkler scheduler with some features [danman] was looking for(eg: it won’t activate if there’s rain in the forecast). Since he wasn’t running it with a Raspberry Pi as recommended, [danman] wrote a Python plugin that runs on his home server as a daemon which listens to TCP port 20000 for connections and then updates the relevant relays. Ok, software done; on to the relay controller box!
Continue reading “DIY Wireless Sprinkler System? Don’t Mind If I Do.”
If you’ve never been a patient at a sleep laboratory, monitoring a person as they sleep is an involved process of wires, sensors, and discomfort. Seeking a better method, MIT researchers — led by [Dina Katabi] and in collaboration with Massachusetts General Hospital — have developed a device that can non-invasively identify the stages of sleep in a patient.
Approximately the size of a laptop and mounted on a wall near the patient, the device measures the minuscule changes in reflected low-power RF signals. The wireless signals are analyzed by a deep neural-network AI and predicts the various sleep stages — light, deep, and REM sleep — of the patient, negating the task of manually combing through the data. Despite the sensitivity of the device, it is able to filter out irrelevant motions and interference, focusing on the breathing and pulse of the patient.
What’s novel here isn’t so much the hardware as it is the processing methodology. The researchers use both convolutional and recurrent neural networks along with what they call an adversarial training regime:
Our training regime involves 3 players: the feature encoder (CNN-RNN), the sleep stage predictor, and the source discriminator. The encoder plays a cooperative game with the predictor to predict sleep stages, and a minimax game against the source discriminator. Our source discriminator deviates from the standard domain-adversarial discriminator in that it takes as input also the predicted distribution of sleep stages in addition to the encoded features. This dependence facilitates accounting for inherent correlations between stages and individuals, which cannot be removed without degrading the performance of the predictive task.
Anyone out there want to give this one a try at home? We’d love to see a HackRF and GNU Radio used to record RF data. The researchers compare the RF to WiFi so repurposing a 2.4 GHz radio to send out repeating uniformed transmissions is a good place to start. Dump it into TensorFlow and report back.
Continue reading “AI Watches You Sleep; Knows When You Dream”