We initially developed this USB atmospheric pressure monitor to study some operating characteristics of Bosch BMP180 sensor. BMP180 is low cost sensor to measuring barometric pressure and temperature. According to the data sheet this sensor can use to measure pressure ranging between 300hPa to 1100hPa. This sensor is introduced couple of years back but still it is popular due to lower cost and simplicity of it’s interface.
This post isn’t another How-To tutorial for a specific sensor because the Arduino community has already produced a considerable number of resources like that. You’d be hard pressed to find any sensor in the DIY market that doesn’t give you a dozen cookbook recipes to follow after a simple Google search. In fact, you get so many results from “How to use SensorX with Arduino” that beginners are overwhelmed because few of those tutorials help people decide which type of sensor suits their skill level. This post attempts to put the range of different options you can use with a Cave Pearl data logger into a conceptual framework, with links to examples that illustrate the ideas in text.
I’ve spent the last year in the ‘uncanny valley’ of the Arduino. That’s the point where you understand the tutorials at Arduino.cc, but still don’t get much from the material on gitHub because trained programmers would never stoop to using the wire.h library when they could just roll their own in native C++ using the avr-g++ compiler. The problem with establishing sensor communication at the level of the TWI peripheral inside the AVR is that there are so many fiddling details to keep track of that it quickly overruns the 7±2 things this average human can hold in his head at one time: Computers aren’t the only things that crash after a buffer overflow! So this post is meant to be a chunking exercise for beginner-intermediate level people like myself who want to get a new sensor working using the standard IDE. I’ve tried to distill it all down to things that I run into frequently, but there’s still a lot of material here: So pour yourself a cuppa before diving in…
It allows us to detect the presence and passage of an object thanks to the combination of a laser diode which emits a light ray and a phototransistor which detects reflected light.
Robotics applications and industrial control systems normally make use of optical systems in order to detect proximity and passing of objects, taking advantage of light interruption or light reflection on a surface of the object to be detected. In this article, we want to show you the project of a laser barrier: however this is not an interruption-type barrier, which needs the object to be detected to pass through a meter and a photodetector, in fact, this is a reflection barrier: in our circuit, a laser projects a ray of focused and infinitely-collimated light and any object passing in front of it will reflect a portion of it, which will be intercepted by a lens on its way back and focused on the sensible surface of a photo-sensible component.
A detailed instructions of how to design a cheap plant watering sensor from LuckyResistor:
I have a couple of plants in flowerpots and this plants not only like some light, they also need water from time to time. Watering this plants is something I often forget, with sad results. There are ready made solutions for this, but I have some objections with all of them. To be clear: There are really smart products out there – it is absolutely nothing wrong with them. It is just as I like to build my own fan controller, I like to build my own plant watering sensor in my very own fashion.
The best thing about owning a 3D printer or CNC router may not just be what you can additively or subtractively create with it. With a little imagination you can turn your machine into a 3D scanner, and using capacitive sensors to image items turns out to be an interesting project.
[Nelson]’s scanner idea came from fiddling with some capacitive sensors at work, and with a high-resolution capacitance-to-digital sensor chip in hand, he set about building a scan head for his printer. In differential mode, the FDC2212 sensor chip uses an external LC tank circuit with two plain sensor plates set close to each other. The sensor plates form an air-dielectric variable capacitor, and the presence of an object can be detected with high sensitivity. [Nelson]’s custom sensor board and controller ride on a 3D-printed bracket and scan over the target on the printer bed. Initial results were fuzzy, but after compensating for room temperature variations and doing a little filtering on the raw data, the scans were… still pretty fuzzy. But there’s an image there, and it’s something to work with.
When you want to play around with a new technology, do you jump straight to production machinery? Nope. Nothing beats a simplified model as proof of concept. And the only thing better than a good proof of concept is an amusing proof of concept. In that spirit [Eric Tsai], alias [electronichamsters], built the world’s most complicated electronic gingerbread house this Christmas, because a home-automated gingerbread house is still simpler than a home-automated home.
Yeah, there are blinky lights and it’s all controlled by his smartphone. That’s just the basics. The crux of the demo, however, is the Bluetooth-to-MQTT gateway that he built along the way. A Raspberry Pi with a BTLE radio receives local data from BTLE sensors and pushes them off to an MQTT server, where they can in principle be read from anywhere in the world. If you’ve tried to network battery-powered ESP8266 nodes, you know that battery life is the Achilles heel. Swapping over to BTLE for the radio layer makes a lot of sense.
Everyone’s favorite viscoelastic non-Newtonian fluid has a new use, besides bouncing, stretching, and getting caught in your kid’s hair. Yes, it’s Silly Putty, and when mixed with graphene it turns out to make a dandy force sensor.
To be clear, [Jonathan Coleman] and his colleagues at Trinity College in Dublin aren’t buying the familiar plastic eggs from the local toy store for their experiments. They’re making they’re own silicone polymers, but their methods (listed in this paywalled article from the journal Science) are actually easy to replicate. They just mix silicone oil, or polydimethylsiloxane (PDMS), with boric acid, and apply a little heat. The boron compound cross-links the PDMS and makes a substance very similar to the bouncy putty. The lab also synthesizes its own graphene by sonicating graphite in a solvent and isolating the graphene with centrifugation and filtration; that might be a little hard for the home gamer to accomplish, but we’ve covered a DIY synthesis before, so it should be possible.
With the raw materials in hand, it’s a simple matter of mixing and kneading, and you’ve got a flexible, stretchable sensor. [Coleman] et al report using sensors fashioned from the mixture to detect the pulse in the carotid artery and even watch the footsteps of a spider. It looks like fun stuff to play with, and we can see tons of applications for flexible, inert strain sensors like these.
In Texas — at least around Houston — we don’t have basements. We do, however, have bilges. Both of these are subject to taking on water when no one is paying attention. A friend of mine asked me what I thought of an Instructable that showed how to make a water sensor using a few discrete components. The circuit would probably work — it relied on the conductivity of most water to supply enough current to a bipolar transistor’s base to turn it on.
It is easy to overthink something like this, so I told my friend he should go with something a little more old-fashioned. I don’t know the origin of it, but it is older than I am. You can make a perfectly good water detector with things you probably already have around the house. My point isn’t that you should (or shouldn’t) construct a homemade water sensor. My point is that you don’t always need to go to the high-tech solution.
On the other hand, this is Hackaday, so I’m sure you want to know how to hack a water sensor out of common household items. The picture probably tells you the story anyway, but if not, read on.
What Do You Need?
The heart of the water sensor is a spring clothes pin. You also need two flat metal pieces. I’ve seen it done with pennies but you could probably use a couple of washers or pieces of scrap metal. I’ve even seen it done with aluminum foil, but I don’t recommend it. There’s one critical piece left: an aspirin. You could probably use some other things, but it has to be something hard enough to keep the clothespin open, but will also dissolve when in contact with water.
You can figure out the rest. You connect wire to the metal contacts, make a sandwich with the aspirin in the middle of the contacts and clamp it together with the clothes pin. If detecting water isn’t your thing, you might enjoy [American Hacker’s] video (see below) that uses the same idea to detect when a door opens.
If you think about it, the point I’m making is one we often see in the comments for Hackaday posts. No, not “That’s not a hack.” I’m thinking more of the latest Raspberry Pi project that turns a light on when it gets dark that will elicit a lot of comments about how you could do that with a 2N2222 (or an op amp, or a 555, or whatever your weapon of choice is).
Generally, we don’t mind projects like that. People don’t need a program that prints “Hello World!” but it is a good way to get familiar with a programming language. By the same token, sometimes doing a simple project with an Arduino, a Raspberry Pi, or an FPGA is more about getting familiar with the development environment and how to apply the tool.
On the other hand, your LED blinker doesn’t need a 2 GHz CPU with 32 GB of RAM running an RTOS. My point with these sensors is the same: there are times you really do need a sensitive, precise sensor. Most of the time you need a lot less. If you aren’t going for an educational project, take some time to think about if you are using a shovel to put sugar in your coffee.
Your Turn: Homemade Sensors
There are lots of ways to make simple sensors. Your turn. What’s your favorite do-it-yourself sensor? Drop a note in the comments and let us know what sensors you’ve hacked out of improbable things.
For the last three and a half Billion years, evolution has built sensors. The nerves on your fingertips are just as good as any electronic touch sensor, a retina is able to detect a single photon, and the human ear is more finely tuned than the best microphones.
At the 2016 Hackaday SuperConference, Dr. Christal Gordon, educator and engineer, talked about the hardware behind our wetware. While AI researchers are still wondering if they have to define consciousness, there’s still a lot that medicine, psychology, and neuroscience can teach us about building better hardware with simple tools, just like nature has been doing for Billions of years.
Processing Data In Hardware
Christal’s talk focused on two senses, vision and hearing. The physical hardware you have for these senses — your eyes and ears — have unique features that allow for very advanced processing right at the first layer of hardware.
Anyone with a basic education has a pretty good idea of how the human eye works. Light enters the pupil, goes through a lens, shines on the retina ‘sensor’, and information travels up the optic nerve to the brain. There’s nothing wrong with this explanation of how the eye works, but like everything you learn in school, it doesn’t go into the details that make the human vision system so amazing.
Unlike the most simplistic explanation of how the eye works, image processing doesn’t exactly happen in the brain. On the retina, there are groups of rods and cones wired together in circular patterns, with the center of the pattern sending a very strong signal to the brain, and the rods and cones surrounding the center sending the opposite signal to the brain.
What does this weird wiring setup get you? In the language of image processing, you get a Mexican Hat function. Practically, you get edge detection and noise rejection, built directly into the hardware.
Eyes and vision processing are one thing, but what about audio. The 8th-grade biology class explanation of the ear tells us the eardrum vibrates, making very small bones in our ear vibrate, which in turn makes tiny hairs in the snail-like cochlea vibrate. These vibrations are sent to the brain. Simple enough.
Following this explanation, all the audio processing then happens in the brain. This isn’t the case, though; the cochlea is finely tuned to different frequencies, and these frequencies translate into phonemes of speech. The cochlea does this by its own physical arrangement and automatically separates a sound into different bins of distinct frequencies. Your ear has FFT in hardware, and a few researchers have already taken this idea of discrete filters and put them into ASICs.
You can do a lot with silicon and sensors, but for most applications evolution already has a solution. In most cases, evolution has come up with a better solution, and we’re happy Christal could speak at the 2016 Hackaday SuperConference on making hardware smarter with this biological-inspired approach to sensing.