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.
Continue reading “Sense All the Things with a Synthetic Sensor”
Zaragoza, Spain hacklab La Remolacha (“The Beet”) sports a logo which responds to human interaction with a beet plant growing in the space. Sensors keep track of temperature as well as humidity for both air and ground, while buttons add more water, plant food, light, and music.
The shape and activity of the visualization responds to the sensors. The higher the temperature, the more folds in the shape. More distortions appear when there’s more humidity in the soil, while rotation speed increases with air humidity. Adding food increases the size of the visualization, and music triggers more vibrations.
An Arduino keeps track of the buttons and humidity sensors, while a nearby computer, connected via USB, sends the data to a node.js server. The data are displayed on the website through the torus visualization, which is done in WebGL.
The beet’s environment also signals the health of the space, because if no one is visiting, no one can feed the plant. On the other hand, could too many visitors actually kill the thing?
The project was created by [Innovart], [Miguel Frago], and [Santi Grau] with help from other folks.
Thanks [Esther Borao Moros] for the tip!
Continue reading “Hacklab’s Logo Changes with the Habitat of a Beet Plant”
TOBE is a toolkit that enables the user to create Tangible Out-of-Body Experiences, created by [Renaud Gervais] and others and presented at the TEI ’16: Tenth International Conference on Tangible, Embedded, and Embodied Interaction. The goal is to expose the inner states of users using physiological signals such as heart rate or brain activity. The toolkit is a proposal that covers the creation of a 3D printed avatar where visual representations of physiological sensors (ECG, EDA, EEG, EOG and breathing monitor) are displayed, the creation and use of these sensors based on open hardware platforms such as Bitalino or OpenBCI, and signal processing software using OpenViBE.
In their research paper, the team identified the signals and mental states which they have organized in three different types:
- States perceived by self and others, e.g. eye blinks. Even if those signals may sometimes appear redundant as one may directly look at the person in order to see them, they are crucial in associating a feedback to a user.
- States perceived only by self, e.g. heart rate or breathing. Mirroring these signals provides presence towards the feedback.
- States hidden to both self and others, e.g. mental states such as cognitive workload. This type of metrics holds the most
promising applications since they are mostly unexplored.
By visualising their own inner states and with the ability to share them, users can develop a better understating of their own selves as well others. Analysing their avatar in different contexts allows a user to see how they react in different scenarios such as stress, working or playing. When you join several users they can see how each other responds the same stimuli, for example. Continue reading “TOBE: Tangible Out-of-Body Experience with Biosignals”
Researchers at Tufts University are experimenting with smart thread sutures that could provide electronic feedback to recovering patients. The paper, entitled “A toolkit of thread-based microfluidics, sensors, and electronics for 3D tissue embedding for medical diagnosis”, is fairly academic, but does describe how threads can work as pH sensors, strain gauges, blood sugar monitors, temperature monitors, and more.
Conductive thread is nothing new but usually thought of as part of a smart garment. In this case, the threads close up wounds and are thus directly in the patient’s body. In many cases, the threads talked to an XBee LilyPad or a Bluetooth Low Energy module so that an ordinary cell phone can collect the data.
Continue reading “Smart Sutures”
[Ken Rumer] bought a new house. It came with a troublingly complex pool system. It had solar heating. It had gas heating. Electricity was involved somehow. It had timers and gadgets. Sand could be fed into one end and clean water came out the other. There was even a spa thrown into the mix.
Needless to say, within the first few months of owning their very own chemical plant they ran into some near meltdowns. They managed to heat the pool with 250 dollars of gas in a day. They managed to drain the spa entirely into the pool, but thankfully never managed the reverse. [Ken] knew something had to change. It didn’t hurt that it seemed like a fun challenge.
The first step was to tear out as much of the old control system as could be spared. An old synchronous motor timer’s chlorine rusted guts were ripped out. The solar controler was next to be sent to its final resting place. The manual valves were all replaced with fancy new ones.
Rather than risk his fallible human state draining the pool into the downstairs toilet, he’d add a robot’s cold logical gatekeeping in order to protect house and home. It was a simple matter of involving the usual suspects. Raspberry Pi and Arduino Man collaborated on the controls. Import relay boards danced to their commands. A small suite of sensors lent their aid.
Now as the soon-to-be autumn sun sets, the pool begins to cool and the spa begins to heat automatically. The children are put to bed, tired from a fun day at the pool, and [Ken] gets to lounge in his spa; watching the distant twinkling of lights on his backyard industrial complex.
There’s a car race going on right now, but it’s not on any sort of race track. There’s a number of companies vying to get their prototype on the road first. [Anurag] has already completed the task, however, except his car and road are functional models.
While his car isn’t quite as involved as the Google self driving car, and it doesn’t have to deal with pedestrians and other active obstacles, it does use a computer and various sensors to make decisions about how to drive. A Raspberry Pi 2 takes the wheel in this build, taking input from a Pi camera and an ultrasonic distance sensor. The Pi communicates to another computer over WiFi, where a neural network operates to make decisions about how to drive the car. It also makes decisions based on a database of pictures of the track, so it has a point of reference to go by.
The video of the car in action is worth a look. It’s not perfect, but it’s quite an accomplishment for this type of project. The possibility that self-driving car models could drive around model sets like model railroad hobbyists create is intriguing. Of course, this isn’t [Anurag]’s first lap around the block. He’s already been featured for building a car that can drive based on hand gestures. We’re looking forward to when he can collide with model busses.
Continue reading “Self-Driving Cars Get Tiny”
We all know that guy (or, in some cases, we are that guy) that can listen to a car running and say something like, “Yep. Needs a lifter adjustment.” A startup company named Augury aims to replace that skill with an iPhone app.
Aimed at commercial installations, a technician places a magnetic sensor to the body of the machine in question. The sensor connects to a custom box called an Auguscope that collects vibration and ultrasonic data and forwards it via the iPhone to a back end server for analysis. Moving the sensor can even allow the back end to determine the location of the fault in some cases. The comparison data the back end uses includes reference data on similar machines as well as historical data about the machine in question.
Continue reading “Listen Up: iPhone Hack Diagnoses HVAC”