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!

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.

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

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.

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.

Dear: LMR

Just to let you know guys it wasn't that long ago I asked my Dad if we could start a robot club at school. My dad brought it up to my princible and he did not have a problem with it. This robot club is probably going to teach people in highschool to build there first robot. I have no idea what robot I am going to teach highschoolers to build.

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Wing is an interactive installation created by Dmitry Morozov  and commissioned by the Center for Art and Media (ZKM) in Karlsruhe, special for GLOBALE: Exo-Evolution exhibition, 2015. It’s a 2,5-meter wing that can be flapped by visitors thanks to compact dermal myLeaographic sensors (sensors measuring the electrical potential of muscles) installed  behind their ears and connected to an Arduino Uno:

The main idea of the project is an ironical and at the same time serious research on the topic of development of new instruments and prostheses as “extensions” of human body and accordingly its possibilities and potentials, which are being revealed by new technologies. At the same time, it’s an attempt to stimulate people to perceive and train the body in a different way, expanding the limits of self-control and self-organisation in order to adapt to the new conditions. At the same time, just like many spiritual practices aiming at the elevation of human soul through deep relaxation and control over seemingly uncontrollable muscles, this project uses the metaphor of flying as a reward for the ability to direct your mind to solving of non-standard tasks.

The Tamagotchi is a thing of the past. Bring your virtual pet into the 21st century with LEDs and an Arduino-compatible processor.

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The post Petduino Is the DIY Tamagotchi You Can Hack appeared first on Make: DIY Projects, How-Tos, Electronics, Crafts and Ideas for Makers.

What happens when a creative technologist wants his family to know he’s thinking about them? He creates a project with Arduino Yún! IMissYou is a simple project transforming a picture in a connected object thanks to a capacitive layer made with Bareconductive Paint and inserted behind the photo. The ‘touch’ is detected by the Arduino through the glass of the frame by a spike in the values (with a basic Capsense library), sent to the internet via wi-fi and delivered to a phone with Pushover.

Martin Hollywood, the Arduino user who made  the project, wrote us:

Looking at the photograph of my family that I have on my desk one day, I missed them and wanted to be home. I touched the photo and realised that somewhere between those was the germ of the idea…

I wanted my family to know I was thinking of them, but I didn’t want to create two products; think GoodNight Lamp – I do love that project. In any case, there was no guarantee they would even notice a ‘blinking’ photo frame responding to my signal. Making the Receive a PUSH notification seemed like a no brainer, but the last time I developed for mobile was iOS 1! There are a number of service apps out there: Pusher, Pushingbox but I decided on Pushover. It had a 7 day trial period and good API support (I’ve since bought a license).

An Arduino Uno appeared at The Tonight Show thanks to a project called Wildfire Warning System created by a 14 years old girl from California. Take a look at the video to discover how  you can detect fires  using a gas sensor and a temperature sensor.

And guess what? Jimmy Fallon knows what an Arduino is! Watch the video:

Last week Temboo just added new Conditions features to its IoT Mode interface, making it even easier to connect your Arduino to the Internet of Things! Now, the functionality of Temboo’s Device Coder has been extended to all 2000+ Choreos in the Temboo Library, meaning that data collected from sensors attached to an Arduino Yún can be used to trigger any cloud process, and responses from the cloud can be used to trigger all sorts of hardware actions on your board.

Using IoT Mode on the Temboo website, you can automatically generate ready-to-run Arduino code to execute Choreos from your board without having to write a single line of code yourself—just specify which board and shield you’re using and what Choreo you’d like to run, and all the necessary code will be generated immediately in your browser. And you can also now visually specify what sort of hardware inputs and outputs you would like to use: the code to connect them to your Choreo will be generated as well.

The visual interface includes a pin selector tool that lets you choose which pins you want to activate and how you want them to interact with the Choreo you are running. The pin selector identifies the pins on your board that are available, and also indicates whether those pins are configured to work with digital or analog I/O. Like the generated code itself, the pin selector interface will change to reflect the board and shield you’ve chosen to work with.

Conditions make it quick and easy to build a massive range of IoT applications, like a thermometer that sends SMS alerts, or a motor that runs when it receives an email. Just specify how you want your pins to interact with the web services you are using, and thanks to Conditions, what you specify will be reflected in a complete, production-ready program generated instantly in your browser. Try it out, and email hey@temboo.com to let them know what you think!

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