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”
[Jesse Burstyn] and some colleagues at Queen’s University and Carleton University (both in Canada) are delivering a paper at the INTERACT 2015 about PrintPut, their system for printing sensors directly into 3D printed objects. Using a printer with dual extrusion and conductive ABS filament, they have successfully formed capacitive touch sensors, digital resistive sensors, and analog resistive sensors.
In practice, this means they can print buttons, sliders, and even touch pads directly into objects. They also have a design for several pressure sensors and a flex sensor. The system includes scripts for the Rhinoceros 3D CAD package. Designers can create a model in any CAD package they want (including Rhinoceros) and then use these scripts to define the interactive areas.
Continue reading “Buttons, Sliders, and Touchpads All 3D Printed with PrintPut”
One of our chief complaints about the Raspberry Pi is it doesn’t have a lot of I/O. There are plenty of add ons, of course to expand the I/O capabilities. The actual Raspberry Pi foundation recently created the Sense Hat which adds a lot of features to a Pi, although they might not be the ones we would have picked. The boards were made for the AstroPi project (the project that allowed UK schools to run experiments in space). They don’t appear to be officially for sale to the public yet, but according to their site, they will be selling them soon. Update: Despite some pages on the Raspberry Pi site saying they aren’t out yet, they apparently are.
Continue reading “Sense Hat Lights up Pi”
Imagine you’re a farmer trying to grow a crop under drought conditions. Up-to-the-minute data on soil moisture can help you to decide where and when to irrigate, which directly affects your crop yield and your bottom line. More sensors would mean more data and a better spatial picture of conditions, but the cost of wired soil sensors would be crippling. Wireless sensors that tap into GSM or some sort of mesh network would be better, but each sensor would still need power, and maintenance costs would quickly mount. But what if you could deploy a vast number of cheap RFID-linked sensors in your fields? And what if an autonomous vehicle could be tasked with the job of polling the sensors and reporting the data? That’s one scenario imagined in a recent scholarly paper about a mobile Internet of Things (PDF link).
In the paper, authors [Jennifer Wang], [Erik Schluntz], [Brian Otis], and [Travis Deyle] put a commercially available quadcopter and RC car to the hack. Both platforms were fitted with telemetry radios, GPS, and an off-the-shelf RFID tag reader and antenna. For their sensor array, they selected passive UHF RFID tags coupled to a number of different sensors, including a resistance sensor used to measure soil moisture. A ground-control system was developed that allowed both the quad and the car to maneuver to waypoints under GPS guidance to poll sensors and report back.
Beyond agriculture, the possibilities for an IoT based on cheap sensors and autonomous vehicles to poll them are limitless. The authors rightly point out the challenges of building out a commercial system based on these principles, but by starting with COTS components and striving to keep installed costs to a minimum, we think they’ve done a great proof of concept here.