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Home automation is a popular project to undertake but its complexity can quickly become daunting, especially if you go further than controlling a few lights (or if you’re a renter). To test the waters you may want to start with something like this home safety monitor, which is an IoT device based on an Arduino. It allows remote monitoring of a home for things such as temperature, toxic gasses, light, and other variables, which is valuable even if you don’t need or want to control anything.

The device is built around an Arduino Nano 33 IOT which has WiFi and Bluetooth capabilities as well as some integrated security features. This build features a number of sensors including pressure/humidity, a gas/smoke detector, and a light sensor. To report all of the information it gathers around the home, an interface with Ubidots is configured to allow easy (and secure) access to the data gathered by the device.

The PCB and code for the project are all provided on the project page, and there are a number of other options available if Ubidots isn’t your preferred method of interfacing with the Internet of Things. You might even give Mozilla’s WebThings a shot if you’re so inclined.

If you want a red piece of paper, or a blue pen, what does that really mean? If you’d like to get more specific, Michael Klements’ Arduino-based scanner lets you quantify colors in numerical RGB values via a TCS34725 sensor.

User interface for the handheld device is extremely simple, with a single button to trigger the sensor and measure colors, along with a 16×2 panel. An optional RGB LED attempts to copy the shade of whatever object you’re aiming at, providing a handy reference to verify it’s working correctly. 

You can see the build process in the video below, first constructed on a breadboard and then placed in a more permanent soldered configuration with a 3D-printed case.

What really happens when you open the refrigerator door? Sure, you know intuitively that cold air escapes, but just how much? And how fast does the food inside actually heat up? To find out, Ryan Bates came up with his own data logging setup using an Arduino Uno, a custom sensor shield, and a microSD card reader.

His device uses a photoresistor to tell when the door has been opened, as well as a DHT22 temperature/humidity sensor to log the air temperature and door status. Along with this, TMP36 sensors are placed around the fridge to get a more granular look at temperatures, including one attached to a pickle jar. 

The results seen in the video below are quite interesting, and more information on the build can be found here if you’d like to try something similar.

Instead of controlling his temperature and humidity display directly, maker Zaphunk did things a bit differently, driving the temperature of each segment with a Peltier element, or thermo-electric cooler (TEC), to change its color. 

Each segment is made out of a thermochromic material, cycling from a black off state to a greenish hue when on, for a device that can—somewhat ironically—show the temperature by changing its temperature.

Ambient conditions are read via a DHT22 sensor, and everything is controlled by a half-dozen Arduino Nanos. This number boards were needed in order to power the nine dual motor drivers that handle the Peltier elements, each of which require two PWM outputs, along with 5 IO pins. 

The display looks great in the video below and Arduino code is found on GitHub.

After obtaining an industrial distance sensor, TUENHIDIY decided to use it as the basis for an interesting visual indicator.

The device communicates with an Arduino Uno via an RS-485 module, and outputs distance values in the form of a 9 x 14 pixel display made out of discreet LEDs soldered onto an LoL Shield.

As shown in the video be low, it does a good job of sensing how far an object is from it on a table, and the 126 LEDs provide a nice brilliant display. 

Code for the build can be found on GitHub if you’d like to make something similar. Seeing as though the sensor used here will set you back close to $1,000, you may want to also consider alternatives like an HC-SR04 ultrasonic module instead! 

Housing exotic plants or animals offer a great opportunity to get into the world of electronic automation. When temperature, light, and humidity ranges are crucial, sensors are your best friend. And if woodworking and other types of crafts are your thing on top, why not build it all from scratch. [MagicManu] did so with his Jurassic Park themed octagonal dome built from MDF and transparent polystyrene.

With the intention to house some exotic plants of his own, [MagicManu] equipped the dome with an Arduino powered control system that regulates the temperature and light, and displays the current sensor states on a LCD, including the humidity. For reasons of simplicity regarding wiring and isolation, the humidity itself is not automated for the time being. A fan salvaged from an old PC power supply provides proper ventilation, and in case the temperature inside the dome ever gets too high, a servo controlled set of doors that match the Jurassic Park theme, will automatically open up.

[MagicManu] documented the whole build process in a video, which you can watch after the break — in French only though. We’ve seen a similar DIY indoor gardening project earlier this year, and considering its simple yet practical application to learn about sensors, plus a growing interest in indoor gardening itself (pun fully intended), this certainly won’t be the last one.

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 [Miguel Frago] and [Santi Grau] with help from other folks.

Thanks [Esther Borao Moros] for the tip!

 

 


Filed under: Arduino Hacks

mellis-aday

At Arduino Day, I talked about a project I and my collaborators have been working on to bring machine learning to the maker community. Machine learning is a technique for teaching software to recognize patterns using data, e.g. for recognizing spam emails or recommending related products. Our ESP (Example-based Sensor Predictions) software recognizes patterns in real-time sensor data, like gestures made with an accelerometer or sounds recorded by a microphone. The machine learning algorithms that power this pattern recognition are specified in Arduino-like code, while the recording and tuning of example sensor data is done in an interactive graphical interface. We’re working on building up a library of code examples for different applications so that Arduino users can easily apply machine learning to a broad range of problems.

The project is a part of my research at the University of California, Berkeley and is being done in collaboration with Ben Zhang, Audrey Leung, and my advisor Björn Hartmann. We’re building on the Gesture Recognition Toolkit (GRT) and openFrameworks. The software is still rough (and Mac only for now) but we’d welcome your feedback. Installations instructions are on our GitHub project page. Please report issues on GitHub.

Our project is part of a broader wave of projects aimed at helping electronics hobbyists make more sophisticated use of sensors in their interactive projects. Also building on the GRT is ml-lib, a machine learning toolkit for Max and Pure Data. Another project in a similar vein is the Wekinator, which is featured in a free online course on machine learning for musicians and artists. Rebecca Fiebrink, the creator of Wekinator, recently participated in a panel on machine learning in the arts and taught a workshop (with Phoenix Perry) at Resonate ’16. For non-real time applications, many people use scikit-learn, a set of Python tools. There’s also a wide range of related research from the academic community, which we survey on our project wiki.

For a high-level overview, check out this visual introduction to machine learning. For a thorough introduction, there are courses on machine learning from coursera and from udacity, among others. If you’re interested in a more arts- and design-focused approach, check out alt-AI, happening in NYC next month.

If you’d like to start experimenting with machine learning and sensors, an excellent place to get started is the built-in accelerometer and gyroscope on the Arduino or Genuino 101. With our ESP system, you can use these sensors to detect gestures and incorporate them into your interactive projects!

BonsaiWatchdog

Bonsai trees are not like other plants. There’s no single watering schedule that can be applied to a bonsai and the best way to tell if the bonsai needs water is to touch the soil. Experienced growers know when a tree needs to be watered by observing the foliage or just by the weight of the pot. If you are not used to taking care of this type of tree, Bonsai Watchdog could be the perfect project for you. It runs on Arduino and Genuino Uno and makes it really easy to monitor the moisture level in the soil.

BonsaiWatchdogDisplay

Thomas Baum, created it and shared it some days ago on the Arduino Community on G+ :

Two pencil leads, an Arduino and a 12864 (ST7565) LCD watches out my little bonsai. The filling level shows how often the sapling need to be watered.
source and discription (in german) you can find here:
http://tiny.systems/categorie/lcdProjekt/BonsaiWatchdog.html

 

tembooM2M

Is there a cool Internet of Things idea that you’ve wanted to try out with your Arduino, but just haven’t had time for?  Building a network that integrates multiple sensors and boards into one cohesive application can be time-consuming and difficult.  To make it a bit easier, Temboo just introduced new Machine-to-Machine programming that lets you connect Arduino and Genuino boards running locally in a multi-device network to the Internet.  Now, you can bring all the power and flexibility of Internet connectivity to Arduino applications without giving up the benefits of using low power, local devices.

temboo-line

Our friends at Temboo now support three M2M communication protocols for Arduino boards: MQTT, CoAP, and HTTP. You can choose which to use based on the needs of your application and, once you’ve made your choice, automatically generate all the code you need to connect your Arduinos to any web service. You can also save the network configurations that you specify, making it easy to add and subtract devices or update their behavior remotely.

With Temboo M2M, you can program flexible distributed device applications in minutes. From monitoring air quality and noise levels in cities to controlling water usage in agricultural settings, networked sensors and devices enable all sorts of powerful IoT applications. You can see it all in action in the video below, which shows how they built an M2M network that monitors and controls different machines working together on a production line.



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