Tag Archives: Raspberry Pi

Using OpenHAB with a Raspberry Pi

Nowadays it is common to have smart home products that you can remotely command to control, adjust, and to switch on and off. The single board computer, Raspberry Pi or RBPi is suitable for building a touchscreen command center to interface with such smart products and to provide a suitable interface for control and task scheduling. As an introduction, the project will consist of a Wi-Fi enabled RGB LED strip. It will interface with an RBPi running OpenHAB. This will allow wireless control to switch the LED strip on or off from a smartphone or any other computer on the network.

With OpenHAB, you can interface with over 150 different existing smart home products. Moreover, OpenHAB is very flexible, is open source, and is free to use. Although you can use OpenHAB on an RBPi, it can easily run on any platform – Linux, OS X, or Windows. That means the same setup can be run from any old laptop or desktop you may have lying around.

For this project, the main components you will need are an RBPi and its touchscreen. An RBPi2 is recommended and you can use the 7-inch Raspberry Pi Foundation touchscreen. Some of the additional things you will need are a microSD card, a USB Wi-Fi dongle, a power supply for the RBPi, the NeoPixel LED strip starter pack, a logic level shifter, an ADAfruit HUZZAM ESP8266, and some hookup wire.

To begin, assemble the screen to the RBPi. This can be somewhat tricky if you do not have instructions. There will be two flat ribbon cables, a large one for the display, and a smaller one for the touchscreen. The large cable from the display connects to the display controller board, and the smaller cable from the display controller board connects to the display. Once this is done, you can screw the display controller board with the RBPi on its back on to the standoffs on the back of the screen. The ribbon cable from the controller board connects to the display connector on the RBPi. Power to the display comes from the GPIO pins on the RBPi, for which you need to connect the 5 V and the GND pins via two jumper wires of red and black color, respectively.

Flash the microSD card with the latest build of Raspbian from the Raspberry Pi website and boot up the RBPi with it. You can now connect your keyboard, mouse, and the Wi-Fi adapter. Configure the RBPi to connect to your Wi-Fi network and get the touchscreen to work. For this, you may need to update and upgrade your OS.

The next step is to install the home automation control software, OpenHAB, and its add-ons – follow the instructions here. Next, solder the logic level converter between the ESP8266 and the NeoPixel LED strip. This is necessary, as the strip works on 5 V, whereas its controller, the ESP8266 works on 3.3 V. Make sure the logic level converter is connected the right way. After this, you will need to flash the ESP8266 with the Arduino IDE.

Now, you can download and install the OpenHAB app on to your phone and set it up to control the RBPi on its IP address.

WD PiDrive for the Raspberry Pi

Most users of the RBPi (Raspberry Pi) prefer to use the single board computer for small and simple tasks suited for their low powered hardware. It is also possible for RBPi users to upgrade their hardware for augmenting functions that need more power. For example, users looking for additional memory space can use traditional SD Cards and USB drives. Now, Western Digital is upping the ante with their PiDrive, a one terabyte hard drive, compatible to the RBPi.

PiDrive is somewhat different from the average storage drive commonly seen in desktops and laptops. In place of the usual SATA interface that comes with a typical hard drive, PiDrive employs a USB 3.0 header, modified for the purpose. That means you can connect the drive to the USB port of the RBPi. However, PiDrive goes a step further. You can connect it to the power port on your SBC. The advantage is that you can now power both the RBPi and the PiDrive from the same source, using a single cable.

Since the SBC RBPi cannot boot from any source other than its microSD card, the WD PiDrive also has a built in 4GB microSD card. You can place an operating system on the card, so that the RBPi can boot from it. WD PiDrive is compatible to both RBPi Model B+ and RBPi 2 Model B.

PiDrive consists of a WD Passport drive with a built-in USB controller in place of the usual SATA interface and comes without any plastic enclosure. Earlier also, others have already toyed with the idea of an RBPi that can boot from and store information to a hoard drive. However, most such ventures needed a powered USB hub to transfer power to the drive. WD has removed the need for the USB hub, making the newly equipped RBPi much neater.

The 1TB PiDrive is available in the form of a kit. Along with the 2.5-inch USB hard disk drive, the kit consists of a 5V power adapter, a USB Micro B to Type A power cord, a WD PiDrive cable and a Class4 4GB microSD card with an SD adapter. However, the star attraction of the kit is the WD PiDrive cable. This specially designed cable supplies the necessary power to the PiDrive and the RBPi at the same time. The included power adapter has adequate capacity to handle the power required by both the SBC and the drive. WD provides a Quick Install Guide for making all the connections easily and correctly.

The microSD card with the PiDrive ships blank and you can install another operating system on it safely, without compromising the existing SD card of your RBPi. That means you can test another OS without losing the files or programs on the original SD card.

To use the WD PiDrive with the RBPi for the first time, you will need to partition it, format the partitions and mount them. You can also store your OS on the drive. For that, you must let the boot loader remain on the SD card, writing only the OS on the PiDrive. The WD Labs Community offers detailed instructions for doing this.

Volumio: Control Your Hi-Fi through a Raspberry Pi

Traditionally, amplifiers connect to loudspeakers through wires. The wires carry the electric currents that make the loudspeakers work to produce sound. So far, wires were also necessary to feed amplifiers from different sources such as CD players, TV sets and others. By placing amplifiers within the speaker enclosure, part of the ugly wiring was taken care, but the wires from the source persisted until wireless methods were discovered.

Introduction of the Walkman and other portable players changed the music scenario forever, bringing it out of the living room and allowing people to carry their music with them. However, there was a limit to the number of songs one could carry on their person. The advent of the smartphones and the Internet opened another door. People could stream music over the net, leaving their collection at home. This was the age of iTunes, Spotify and Beats Music, facilitating listening to music wherever you may be.

Most often, these new methods prove expensive for those on a budget, and they are forced to bypass the newer ways of consuming music. An RBPi (Raspberry Pi) is a great help in these cases, simply because the single board computer is affordable, flexible and of a convenient size. Its flexibility makes it a perfect fit for use as a home audio solution and you can control your music wirelessly without having to invest in expensive high-fidelity stuff.

An RBPi gives you many modes of selecting songs to play and the manner in which they are played. For this, the RBPi uses a specially tailored Operating System by the name of Volumio. The major attraction is the nice and simple cross-platform web interface through which you can control music.

The RBPi sits as a controller just in front of the amplifier. It can pick up songs from a USB stick plugged into one of the USB sockets, select it from your local home NAS or take your picking from Web Radio. For the last part, you will need a Wi-Fi dongle to connect the RBPi to the Internet.

Volumio is easy to set up, as not much of advanced functions or graphics are to be handled. Simply download the Volumio disk image, transfer it to your microSD card and use it to boot up the RBPi. You will not require a keyboard, mouse or monitor to set up the software, as the entire configuration is possible through the web interface of Volumio.

Use your computer to connect to Volumio. You can find it by connecting your computer to the same network where you have your RBPi plugged in. You may also use Volumio over a wireless network, for which, you will have to first connect to the RBPi via Ethernet to configure its settings for use with a Wi-Fi dongle. This also allows you to control the software with the browser on your smartphone – simply type in the URL ‘http://volumio.local’ in your browser.

Using the RBPi makes it simple to select songs and set up other parameters for playing them on your home Hi-Fi system. As an advanced arrangement, this is affordable and one can easily modify it to suit specific needs.

Build a Humanoid Robot from Raspberry Pi

Raspberry Pi or RBPi is the ubiquitous low-cost, credit card sized single board computer with huge potential starting from teaching youngsters computer programming to driving robots on Mars. However, when Tyler Spadgenske tried his hands on RBPi, he used the SBC to create Andy – a completely open-source humanoid robot.

Tyler has tried to make Andy a connected robot. Andy can connect to humans through speech, using language as humans do – for answering questions. With access to the Internet, he (Tyler assures Andy is male) can also talk to client programs over the Web. With ability to connect via Bluetooth, Andy communicates with other robots such as the Mindstorms NXT.

Using a bipedal mechanism that offers him mobility, Andy can do additional tasks such as moving stuff. Of course, Andy has his limitations, but then, he can collaborate with other robots to get those things done, which he cannot. Tyler has given Andy only speech as the user interface, since he feels a humanoid should have no other. However, that does not limit Andy from interfacing with other computers over the Internet, because basically, he is a computer himself.

Initially Tyler was using Robosapien for Andy’s bipedal movement, but that did not work out satisfactorily. He is using a new bipedal system using SolidWorks. Later, Tyler plans to add a torso, a head and arms for Andy, again using SolidWorks and 3D printing.

Starting up Andy is very simple – flip the switch on his back to the on position. Andy has LiPo batteries rated for 11.1V, 1.3A and 1300mAH. These power his motors through the L298 motor drivers, which the RBPi drives. As soon as the RBPi receives power, which is regulated with a UBEC, it starts executing Andy’s software. This begins with some configuration checks such as for starting the server and running some modes. Then Andy settles down and prepares to listen to his microphones.

Now, Andy is up and running as a state machine. He will listen to commands from either his microphones or his server – first converting any command received from either to text and then executing it.

After converting the command to text form, Andy interprets it by comparing it to the command set in his repertoire. That gives him the correct function he must execute for a specific command. For example, for a shutdown command, Andy initiates a complete sequential software and hardware shutdown, ultimately switching himself off. For any other command, however, Andy executes it and then goes back to wait for commands from his microphone or server.

Andy’s brain, the RBPi, controls almost everything for him, including speech recognition and motor control to Andy’s software. Andy has three L298 motor drivers, with each capable of controlling and driving two motors each. Therefore, Andy is capable of driving a total of six motors. As the RBPi had only a limited GPIO pins, Tyler had to expand them using an MCP23017 chip.

Tyler plans to give Andy 10 degrees of freedom with the new SolidWorks hardware. His new features will include monitoring the battery voltage, a power on LED, an LED output with five segments and ten servos – six for the arms and four for the legs.

Comparing Raspberry Pi to Banana Pi

The new version of the hugely famous single board computer, the Raspberry Pi or the RBPi as it is commonly known, brings many improvements to its users. The RBPi version 2, Model B has improved on the CPU, added RAM, more USB ports and GPIO pins. However, the increasing popularity of the RBPi has sparked off a trend with several other manufacturers chipping in to make available SBCs with features similar to and sometimes surpassing those of the RBPi. The Chinese manufacturer LeMaker is one such manufacturer producing a competing product called the Banana Pi.

The Banana Pi manufacturer, LeMaker, took pains to ensure compatibility with the RBPi while improving on the performance. That made LeMaker replace the CPU with a superior one operating on dual cores clocked at 1GHz. That is, until the manufacturers of the RBPi responded with a V2, Model B that has a CPU with four cores firing away at 900MHz.

That made the difference in performance more dependent on the software running on the individual SBCs. The video processor in the new RBPi is somewhat more advanced as compared to the Mali GPU in the Banana Pi. Therefore, those using HDMI out for playback or media streaming will find the RBPi a better choice.

On the other hand, people requiring access to a large storage for consistent read and write, will find the Banana Pi more convenient. The Banana Pi has a SATA port that allows connecting a large hard drive, offering the faster and more permanent options of a mass storage device. Compare this to the MicroSD storage and USB interface that the RBPi relies on for interfacing to memory devices.

Although both devices have Ethernet ports built-in for wired network connectivity, the Banana Pi has gigabit capability. However, that does not tip the scales against the RBPi much, since many devices are yet to have gigabit support anyway. The Pro version of the Banana Pi, however, can simplify a lot of projects with its built-in Wi-Fi and 802.11n support. While with the RBPi, you need to plug in a separate Wi-Fi module, which will tie up one of its USB ports.

The design concept of the RBPi centers on its ease of use and its budget-friendliness. That has made it such an extremely popular entity in the maker community. A large support base of users enforces the usefulness of the device, providing it with a wealth of information on creating software, hardware and innumerable tutorials built specifically for the RBPi. Although such resources do exist for the Banana Pi as well, they are neither as common nor so comprehensible. Moreover, the Banana Pi is somewhat harder to set up when compared to the RBPi setup.

For those planning to use a Banana Pi as a drop-in replacement for the RBPi, there is disappointment in store. Dimensionally, as the Banana Pi is larger than the RBPi, replacement entails a bigger case or an expanded slot for the Banana Pi. A bigger worry is the placement of the CPU, which, for the Banana Pi, is on the bottom side of its board rather than on the top. That may mean additional arrangements for heat removal, as the CPU is the biggest heat generator in any SBC.

LIDAR and the Raspberry Pi

For hackers and DIY enthusiasts, it is always a challenge to make correct measurements between their robots and nearby objects such as an autonomous vehicle. Estimating the distance is important for the robot to make a decision about avoiding bumping into obstacles. Although this may be considered trivial for a small robot running into a wall, it could turn out deadly for the same robot encountering an autonomous vehicle.

In 2013, NASA held a competition called SRR or Sample Return Robot, where several entrants used various techniques for making measurements using visual aids such as cameras. Two entrants used LIDAR, which can also be used with the single board computer, the Raspberry Pi, or RBPi.

Although using similar methods, LIDAR uses light for measurements, rather than its forerunner RADAR or Radio Detection and Ranging. According to the Merriam-Webster dictionary, LIDAR was first used 1963 for measurement of clouds and Apollo 13 used it to measure the surface of the moon. Since then, the reductions in the size of lasers have led to additional uses, including the military using LIDAR for range finding.

A scanning LIDAR uses the laser beam to sweep a wide area both vertically and horizontally. The feedback provides a cloud of distantness measurement points. This is similar to aircraft control radar swinging a beam through the sky. There are two principal methods for measuring distances using a laser. One is to measure the time of flight of a laser pulse and the other is to measure the angle by which the laser beam deflects.

For the time of flight measurement, you send out a pulse of laser and measure the time for the signal to return. That time divided by the speed of light gives the distance the laser traveled out and back. The distance to the object is then half the calculated distance. Given the high speed at which light travels, it is difficult to measure distances below a meter using lasers, because light would be returning in about seven nanoseconds. LIDAR uses continuous modulation of the laser by amplitude or frequency and measures the phase difference between the transmitted and received signals. This process using modulation allows measurements down to centimeters.

The LIDAR is actually a sealed unit with a motor at one end that spins a turret at about 300 RPM. Inside the turret are the laser and the receiving sensor. Spinning allows a 360-degree scan of the surrounding area. There are two optical ports out of the turret, corresponding to the laser and the sensor. A two-pin connector provides power to the motor. Another four pin connector is for supplying the inner control and serial interface circuits with 5V and 3V3 DC.

WiringPi is a library of programming the GPIO on the RBPi that offers an absurdly simple and minimal user interface for handling the LIDAR. Additionally, WiringPi is suitable for several RBPi models. Another advantage in using WiringPi is its ability to do hardware PWM on one GPIO pin of the RBPi. Another possibility is to use PID or Proportional Integral Differential control system in a loop to maintain constant speed of the turret motor.

Raspberry Pi and Mathematica Control Telescopes

The single board computer, the Raspberry Pi or RBPi is a versatile device helping youngsters learn computer programming. Its advantages do not stop there, because many hobbyists and DIY enthusiasts also use the RBPi for their numerous innovative projects. For example, Tom Sherlock, an amateur astronomer, has put the RBPi to good use for controlling his telescope. Along with the RBPi, Tom uses Mathematica and the Wolfram language for his telescope control.

Amateur astronomers such as Tom use Mathematica in their hobby to process and improve the images they take of planets and nebulas. They use the Wolfram language to control their astronomical hardware. This consists mainly of controlling the drive on the telescope mount, as this is necessary when automating an observing session.

The process is an important one for the amateur astronomers who use their computerized telescopes for hunting down transient phenomenon such as supernovas. Existing software can take care of the several tasks required by astronomers such as locating objects, managing data and performing image processing, However, automating all the various tasks that an observation session needs, is a great help.

Mathematica is a very useful tool for astronomers. It helps in automating and unifying many of the above operations. Within Mathematica, you have a huge amount of useful astronomical data, which includes the coordinates of several thousand planets, asteroids, galaxies, nebula, and stars. The image handling and processing capability of Mathematica is extremely useful when processing astronomical data.

Tom had earlier interfaced with telescope mounts using an existing library of functions known as ASCOM, a powerful tool for driving domes and filter wheels, mainly associated with astronomy. However, ASCOM has to be pre-installed on a PC and therefore, is rather limited in its use. Using Mathematica allows one to drive the telescope mount directly from any platform and does not need any special setup.

According to Tom, most telescope mounts follow one of two serial protocols for their control. These are the Celestron NexStar protocol or the Meade LX200 protocol. Many non-Meade telescope mounts, such as those from Astro-Physics and Losmandy, also follow the LX200 protocol. Those produced by the Orion Atlas/Sirius family of computerized mounts follow the NexStar protocol just as the Celestron telescopes and mounts do.

The LX200 protocol requires the right ascension (RA) function specified by a string such as HH:MM:SS and the declination (Dec) by a string in the form of DD:MM:SS. These are the basics for slewing the telescope to a target at coordinates specified by the RA and the Dec strings.

You will need an inexpensive USB-to-Serial adapter for creating the RS232 port that the RBPi does not normally have. You also need a small wireless network adapter that fits in the RBPi USB socket. As RBPi uses the Linux operating system, it is easy to use the Wolfram language code for controlling the telescope through the serial port. Additionally, the RBPi can be networked wirelessly. That makes it possible to control it from inside the house, necessary when the weather outside is cold.

Does the Raspberry Pi 3 Run Hotter than the Raspberry Pi 2?

Several people are now eagerly using and testing the new SBC or single board computer from the Raspberry Pi Foundation, the Raspberry Pi Model 3, or RBPi3. Although the overall response has been of enthusiastic welcome, there are some notes of concern as to the new board running rather warm under load. Michael Larabel has run some tests to compare and show just how warm the RBPi3 can get when compared to what the RBPi2 does. Finally, we suggest some remedies for cooling down the RBPi3.

Michael has used the Phoronix Test Suite while monitoring the SoC temperature on both, the RBPi3 and RBPi2, when running the same benchmarks in the same manner for both. One important point to note is the RBPi2 was running inside its case, while the RBPi3 ran completely exposed.

The average temperature of the SoC on the RBPi3 under load was 61∞C, peaking at 82∞C. Under the same conditions, the RBPi2 (within its case), recorded an average temperature of 48.9∞C, peaking at 59∞C. That means the RBPi3 under load, operating in open air, was peaking at more than 20∞C, over its predecessor. That also means if you are planning to put the RBPi3 inside a case when operating, it might make matters worse.

Therefore, if you are planning to stress your RBPi3 routinely, you might consider the following options to keep the RBPi3 temperature down.

Wait for the Linux 4.6 kernel

According to Eric Anholt from Broadcom, the VC4 DRM driver is undergoing an update to get into the Linux 4.6 kernel merge window. This will include a significant 3D improvement in performance and a fix to the HDMI hotplug detection for the RBPi2 and RBPi3. The improvement in performance comes from the RBPi kernel DRM driver pairing with the user-space driver of the VC4 Gallium3D.

Better performance is mainly due to the pipelining, binning and rendering jobs from using xllperf or GLAMOR over OpenGL, which boosts the performance by over 20-30%. The hardware is capable of running separate threads simultaneously for binning and rendering, while OpenGl waits for them to complete before it submits the next job.

Wait for the 64-bit Raspbian

Michael has done some tests to show that there is a conclusive evidence of performance difference between using 64-bit software on supported hardware over a 32-bit operating system. Since the new RBPi3 is a 64-bit system at hardware level, the results should apply to this SBC as well.

For the test, Michael has used an Intel UX301LAA ultrabook with 8GB of RAM and 128GB SanDisk SSD. The operating system was Ubuntu 16.04 daily ISO build, in 64-bit and 32-bits version.

The average power used by the 64-bit system was 30.1W compared to 31.9W by the 32-bit system. Lowest power consumption with 64-bit build was 8.5W compared to 9.4W. The peak power consumed by the 32-bit system was higher at 54.3W compared to 49.7W by the 64-bit system.

Use a Heat Sink to Cool the RBPi3 immediately

For immediate relief, you can use the passive heatsink available that fits the RBPi2 as well as the RBPi3. At $5 from Amazon, this solution is cost-effective in addition to being immediately available. Moreover, the heatsink will drop the temperature of the SoC by almost half.

Cayenne on a Raspberry Pi

If you are building projects for IoT or the Internet of Things, a single board computer such as the Raspberry Pi, also known as the RBPi, can be a great asset. Moreover, with Cayenne installed on the RBPi, you have a drag-n-drop IoT project builder that the developers of the Cayenne software, myDevices, claims is the first in the world.

Therefore, now it is easy to connect your RBPi to a mobile or online dashboard. On the other side, you have a breadboard ready to connect relays, lights, and motion sensors. Of course, you have always had the freedom to write an application, read multiple pages of documentation, and take time to learn new programming languages, write pages of code, and then debug them to make it all work together. Alternatively, you can reduce the time you spend preparing for your project, because Cayenne helps to get your project up and running in a fraction of the time, and you can build your automation projects in minutes.

With Cayenne, myDevices makes all this possible, because they created Cayenne for makers and developers eager to build and prototype amazing IoT projects with their RBPi, as quickly as possible. Users get a free Cayenne account, which allows them to create unlimited number of projects. There is also a full-fledged IoT maker support capability that allows remote control of sensors, actuators, motors, and GPIO boards.

On the free account, you can also store unlimited amount of data that the hardware components collect including triggers and alerts, providing all the tools necessary for automation. That allows you to set up custom dashboards and threshold alerts capable of highlighting your projects with fully customizable drag-n-drop widgets.

According to myDevices, Cayenne is the first of its kind of builder software that empowers developers to use its drag-n-drop features for creating quick IoT projects and host their connected device projects. Cayenne allows remote control of hardware, displays sensor data, store data, analyze it, and do several other useful things.

In the Cayenne platform, users can find several major components, such as:

The main Application – useful for setting up and controlling IoT projects with drag-n-drop widgets.
The Online Dashboard – set this up through a browser to control your IoT projects.
The Cloud – useful for storing devices, user and sensor data, actions, triggers, and alerts. Additionally, it is also responsible for data processing and analysis.
The Agent – useful for communicating with the server, hardware, and agent for the implementation of outgoing and incoming alerts, triggers, actions, and commands
Whenever you press a button from the online dashboard or the Cayenne app on your mobile, the command travels to the Cayenne Cloud for processing and travelling to your hardware. The same process takes place in the reverse direction as well. Cayenne offers users plenty of features.

You can connect to your IoT through Ethernet, Wi-Fi, or mobile apps. It is possible to discover and setup your RBPi on a network via Ethernet or Wi-Fi. Dashboards are customizable and widgets are drag-n-drop. It is possible to remotely access your RBPi, shut it down, or reboot it. Users can add sensors, actuators, and control extensions connected to the RBPi, and many more.

EEG Controlling Music through Raspberry Pi

Imagine controlling Pandora with your brainwaves. Whenever a song comes up that you do not enjoy, make it switch to the next one. All you need is an EEG sensor, a pianobar and a single board computer such as the RBPi or Raspberry Pi. Once you train the RBPi to differentiate the bad from good music, you are good to go.

You need to train the Bayesian classifier to recognize good music from the bad. However, basic machine learning techniques do not always turn out very good. Therefore, with this time-series data, you can use it in sequences to reduce false positives.

Using an EEG headset to control songs you dislike is great, especially when you are moving around or doing something away from your computer. You simply slip on the Mindwave Mobile headset from the Brainwave Starter Kit and use the included app to see your brainwaves change in real-time on your mobile. You can monitor your levels of relaxation and attention while watching the response of your brain when you are listening to your favorite music. The Brainwave store has multiple brain training games and educational apps, which are classified according to age and personal interests.

Data from the Mindwave Mobile headset travels via Bluetooth to communicate wirelessly with the RBPi. Using the free developer tools available online from NeuroSky, you can write your own programs to interact with the Mindwave Mobile headset. On the Mindwave Mobile, you can see the EEG power spectrums of alpha, beta and other waves from your brain. With the NeuroSky eSense, you can even sense eye blinks and differentiate between attention and meditation states.

When using the EEG headset with the RBPi and a Bluetooth module, you can record data of some labeled songs that you like and some that do not appeal to you. From the Mindwave headset, the RBPi will get data on waves from your brain such as the delta, theta, low alpha, high alpha, low beta, high beta, mid gamma and high gamma. It will also get an approximation of your meditation and attention levels using FFT or Fast Fourier Transform. Additionally, the headset also provides a skin contact signal level.

It is difficult to make out much from the brainwaves unless you have received adequate training to do so. Machine learning helps here, as you can use software to differentiate good music from the bad. The basic principle is to use Bayesian Estimation to construct two multivariate Gaussian models, one based on good music and the other representing bad ones.

Initially, the algorithm may only be accurate about 70-percent of the time. Although this is rather unreliable, you can use the temporal data and wait for say, four simultaneous estimates before you decide to skip the song. The result is a way to control the songs played, using only your brainwaves.

Pianobar on the RBPi controls the music stream to Pandora. You start pianobar and then start the EEG program using python. It will tell you if the headset is placed properly on your head since it gives a low signal warning. Once it detects a song, it will skip it once it detects four bad signals in a row.