Algorithmic Overview

Algorithmic Overview: Abstract

This paper will be an investigative overview of one of today’s most ubiquitous and often misunderstood mathematical/logistical tools: the algorithm. An expansive subject that can quickly become complicated and lost in jargon, this research will work as a general overview, moving through key concepts while providing a few detailed examples for illustrative purposes. Beginning with an explanation of the general purpose of algorithms, and their logical structure, a brief survey of applications, including search engines like those of Google; realistic graphics, animation and effects in movies and video games; data-mining and cataloging (nsa, cia, Facebook); dating website bio-matching; hight-speed stock market trading (buy/sell, ‘short selling’); physics, astronomy, including some large-scale modeling systems. Discussion of evolutionary algorithm function and component parts follows, with examples of effects. Lastly, pitfalls and real-world exemplars are provided, detailing instances of algorithms gone amok and aftermath(s) — for instance, the financial “flash crash” of 2010.

 

Please click this line to read a research paper on algorithms.

Click this line to view the Alogrithm slideshow presentation from class.

C&C Algorithms Abstract

 

Quantified Self

Quantified Self Movement

 Quantified Self is data aggregation of one unit of being (a conscious one). Data can be varied in different forms, such as data extracted from different body organs, or data from your eating habits, activity, etc. Quantifying self isn’t a new thing, since the development of human brain, we used to take data from a sick person, or our children in cave’s walls. Coming little further in history, I would like to use a more precise example, athletes recorded their eating habits and exercises since official sports have been around. But what is new is the technology that enables us to gather data and use it in a much more organized and precise way. This is a really exciting moment to track your different behaviors and observe how they affect your well-being. We are able to track hyper specific behaviors like we never could before.

 The great thing about this is you having access to your own data, not monster corporations. The movement is all about empowering individuals, create and digest data to effect personal change.

 The inputs from you to the data gatherer could be varied. The most popular ones could be the food consumed or your mood states, your blood oxygen levels, or even your mental and physical performance. It has become a very hot season for self-monitoring and self sensing devices that adopt wearability. These devices usually use different techniques which I shall discuss later.

Brief History

This idea of using wearable sensors and wearable computing started with lifelogging. The idea fostered by Steve Mann, PhD, and a professor at the university of Toronto. In early 1980s, he was the the first person to capture continuous physiological data with first person video from a wearable camera which led to wireless webcam. Lifeloggers typically wear computers in order to record their entire life. In 1998, he started a community called Lifeloggers with 20,000 members.

 But the term quantified self does not appear until 2007. The term was proposed by Wired Magazine editors Gary Wolf and Kevin Kelly as a “collaboration of users and tool makers who share an interest in self knowledge through self tracking.” They later established Quantified Self labs based in California, where they created a world wide community and organized conferences and meetings.

 

5 Pillars

There are five playing elements or pillars to achieve the best results in the scope of self tracking; big data, sensors, data visualization, gamification and mobile apps.

 1. Big data: “big data is the new oil” is a phrase we been hearing a lot in recent years. Data is what constructs and establishes this movement. Individuals are already creating huge amount of data, but what is about to change is the increasingly availability of technology to use the data in a creative and compelling way. The core of this movement is empowering individuals through better acknowledging their self potentials. Here is an example from David El Achkar who gathered data from personal, work and social activities. http://vimeo.com/78020552

 2. Sensors: Tim O’Reilly, the founder of O’reilly Media, the man behind the most important technology publications pinpoints the next biggest thing would be sensors. He anticipated 2013 in a very clever way back in 2009. Sensors getting smarter, more efficient and cheaper and of course tinnier, which makes them adorable. I will discuss sensors more deeply later on this paper. But let me tell you about BioStamp before that. BioStamp is a collection of sensors that can be applied to the skin like a band-Aid. The sensors collect data such as body temperature, heart rate, brain activity, and exposure to ultraviolet radiation. It uses near field communication, a wireless technology that transfers data to nearby devices.

3. Data Visualization: all data gathered by all these technology must be organized and visualized in a compelling way in order to be better understood and digested. If any impact needs to be made, it must occur on this level. As an example, I would like to use Nicolas Felton’s map of his geolocational data through a month.

4. Gamification: gamification is a technique of using game mechanics in a non-game context in order to increase user engagement, return on investment, timeliness and also learning. A really good example of it would be Khan Academy. It’s involving in the real world qualification where it helps to provide user competition, for user who enjoy comparing their results with others and challenge their mates. This will also help users to beat own records and fight for their capability. A good example of it would be Nike+ where you can challenge your friends and family in order to keep yourself motivated.

5. Mobile: mobile is where everything ends through this system. The widespread mobile and tablet UI’s are the end point for delivering all the values and calculations back to user. Mobile apps are being rock stars in this movement.

 

Sensors

To better understand the achievements in sensing technology and the bright future of it, I would like to start with an example, the evolution of microphones. Early telephones relied on carbon microphones, invented by Thomas Edison. Today’s smartphones are based on micro electro-mechanical or MEMS mics. They basically do the same thing, which is converting sound waves into electrical signals. But now they are doing much more than that, amazing things from gesture tracking to tuning into signals from inside the body. They can act as versatile sensors.

 For example: StressSense is a software developed by a Cornell University group, works similar to your ears. It analyzes the subtle changes in pitch, amplitude and frequency as well as your speaking rate resulted by stress. It’s an Android based app which gives you stress levels.

EEG Sensors

 There are also different types of sensors, each built for specific data for self-tracking. I will briefly explain the most popular ones along with examples of them. Electroencephalography (EEG) sensors record the electrical activity among the scalp. They measure voltage fluctuations resulting ionic current flows within the neurons. Although they are in their early developmental stages, but they have attracted a lot of enthusiasts. The biggest problem with this technology is writing a precise algorithm to conclude the best results. Another problem in most cases is that users must be trained.

Melon is a good commercial example for it, it’s a headband that taps into your brain’s inner workings to show you how well is your mental focus. It has a trio of electrodes for sensing brainwaves, a NueroSky chip for filtering electrical noise and Bluetooth 4.0 for communication. It also has an iPhone app which gives you the focus graph.

melon-headband

Accelerometers

Accelerometers are another type of popular sensors. They measure proper acceleration associated with weight phenomenon. Misfit Shine is an elegant activity tracker that you can sync with your smartphone by placing it on your phone. The algorithm is written in the way to track cycling and swimming in addition to just steps.

misfit-shine

LED Projection

LED projection like microphones acting as highly used sensors. AIRO has developed a wristband that can track nutrition, stress, sleep and exercise. The wrist sensor projects light from an LED into the bloodstream to detect metabolites associated with food intakes on their optical signatures and can distinguish between carbohydrates, fats and proteins.

airo

ECG Sensors

For ECG (Electrocardiography) sensors, Omsignal is a good commercial product as an example. ECG is a transthoracic interpretation of the electrical activity of the heart over a period of time. The company is working on a full apparel line that continuously monitors physical activity, ECG data, and breathing patterns, transmitting that data to an accompanying smartphone app. In addition to raw bio data, the user will receive interpretations of tension levels, or “emotive” states, and subsequent prescriptions for how to improve.

screen-shot-2013-07-17-at-3-42-12-pm

GSR Sensors

Galvanic Skin Response (GSR) sensors implemented in some products measure the electrical conductance of the skin, which varies with its moisture. The sweat glands are controlled by the sympathetic nervous system, that’s why they can interpret nervous states. Back to the point BodyMedia’s armband which is the collection of different sensors including GSR is a activity tracker that measures skin temperature, heat flux and overall movement. Jawbone has recently acquired the company for more than $100 million.

1208_tech-fitness-bodymedia-armband_485x340

Others

There are many other different sensors like muscle/ electromyography sensors that are being used by the industry, but are not as important as the ones we already discussed in this paper.

During my research I found e-health, an amazing shield for Arduino and Rasberry Pi produced by Cooking Hacks. It allows users to perform biometric and medical applications. 10 different sensors come with the pack: pulse, oxygen in blood (SPO2), airflow (breathing), body temperature, electrocardiogram (ECG), glucometer, galvanic skin response (GSR – sweating), blood pressure (sphygmomanometer), patient position (accelerometer) and muscle/eletromyography sensor (EMG). Really cool, right?

e-health

 Conclusion

The human mind is not powerful enough to keep track of the countless factors that go into producing an emotional state. Timeline graphical analysis can help to identify potential confounding uncontrolled variables that may be contaminating the results of an experiment. Quantified Self technology enables individuals control all these variables and use it for future experiments.

Quantified Self is not limited to biometrics, every data that can make some impact on our living quality worth analyzing. Now social network companies offering users graphical analysis of their online activity like LinkedIn’s Inmaps.

There is a bright future for the industry and an exciting time for industrial and product designers to get involved in the movement. There has been over 30 million wearable, wireless monitoring devices sold in the US last year according to ABI Reseach analyst Jonathan Collin. This number will increase to 160 million by 2017.

 Refrences

http://spectrum.ieee.org/biomedical/devices/how-i-quantified-myself

http://www.wearable-technologies.com/2013/11/wearable-technologies-news-roundup-october/

http://quantifiedself.com/guide/tag/gadget

http://www.economist.com/node/21548493

http://spectrum.ieee.org/at-work/test-and-measurement/tracking-the-quantified-self

http://www.topcoder.com/blog/2013-your-year-to-innovate-in-the-physical-realm/

http://www.wearable-technologies.com/2012/03/clever-plasters/

http://www.forbes.com/sites/jessedraper/2013/08/01/a-melon-for-your-melon-wearable-tech-for-your-brain/

http://www.misfitwearables.com/

http://www.bodymedia.com/

 

Pdf file of my presentation:

Ardavan Mirhosseini – Research Presentation 1

Kinect! Translating Information Through Gesture & Sound

Research Presentation: Kinect

Presented: October 2013

Kinect Research Report draft

Research Presentation: Mobile Apps in the Game World

What is an App:

The term “app” has become popular over the years and in 2010 and was listed as “Word of the Year” by the American Dialect Society.

‘App’, in the sense that we mean it today, did not exist before the iPhone was introduced in 2007. Apps are relatively lightweight programs, specifically designed to run on mobile platforms such as the iPhone and Android phones.

History of Mobile Games:

The mobile game genre essentially began in the early 90s when design and technology companies, such as Texas instruments, began to embed the snake game in their devices. The pixilated reptile that grew in size while gliding through a tiny maze captivated users so much that Nokia decided in 1997 to become the first mobile phone provider to include a game in one of its models. 350 million mobile phones have offered snake as a standard feature.

Snakes popularity inspired so many companies that they began to work on technology, informally knows as WAP (Wireless application protocol), which would enable mobile phones to transfer game-related data via a remote server. The game developers began to explore and understand the possibilities for fast action and multiplayer mobile-based games.

The mobile games turned corners when iPhone was launched in 2007 and in 2008 iPhone created a wide open market for third- party titles, where the barrier to entry for developers was low and games costed relatively little money for consumers. The app store revolutionized the sector by establishing an easily- accessed direct connection between developers and consumers.

Similarly, thousands of developers create a variety of apps for Android, a mobile operating system launched by the Open Handset Alliance. Google’s Android Market enables users to access the more than 700,000 apps available for the system.

Overview of Mobile Games:

As smartphone and tablet penetration have significantly grown over the last few years, the performance metric for playing games has changed from quality of graphics to convenience and ease of play. People want to be able to play games on-the-go like when they’re waiting in line or have a few spare minutes in between class.

Such a desire for portability and convenience has created a genre of mobile games that are attracting new, “casual” gamers – ones that never played hard-core games on PCs or consoles but are now finding themselves addicted to simple, cheap, quick, pick-up-and-play mobile games they can play whenever they want from wherever they are. But without the expensive, up-front purchase of consoles and games, mobile games have looked to new business models

What’s most remarkable about this growth is that 80% of total app revenues now originate from freemium products from the mobile games.

“Games count for the vast majority of revenue for Google and Apples stores,” “Maybe two or three years ago, you would pay $1 or $2 for a game, but there was no opportunity for them to charge you more. Now they give it to you for free, then keep charging you for additional features.

Research Report Document

 

Research Presentation – Audiovisual Communication

Abstract

The research idea is inspired from Dushan’s Project 2, the sound drawing project. Also, there are many sound visualization projects which sound could be transferred to images. I was thinking about if there is a way could transfer images back to sound accurately so that we can achieve a two-way communication between sound and images. The research shows that sound and images could be translated through audio frequency and sound spectrum. In order to solve the problem, we are still facing three challenges or steps.The research presentation conducts research in each of the step and collects the useful information and tools. After the research, it shows there is possibility to make the idea come true.

 

Research Inspiration

 The research idea is inspired from Dushan’s Project 2, the sound drawing project. Also, there are many sound visualization projects which sound could be transferred to images. I was thinking about if there is a way could transfer images back to sound accurately so that we can achieve a two-way communication between sound and images.

Screen Shot 2013-12-02 at 5.21.55 AM

 What is Sound Visualization?

 Music visualization is a feature found in electronic music visualizers and media player software, generates animated images based on a piece of music. The images are usually generated and rendered in real time and synchronized with the music as it is played.

Visualization techniques range from simple ones to elaborate ones. The changes in the music’s loudness and frequency spectrum are among the properties used as input to the visualization.

Brief History of  Sound Visualization 

The first electronic music visualizer was the Atari Video Music introduced by Atari Inc. in 1976, and designed by the initiator of the home version of Pong, Robert Brown. The idea was to create a visual exploration that could be implemented into a Hi-Fi stereo system. It is described in US 4081829. Music visualization was first pioneered in Great Britain by Fred Judd.

Music and audio players were available on early home computers, Sound to Light Generator (1985, Infinite Software) used the ZX Spectrum’s cassette player for example. The 1984 movie Electric Dreams prominently made use of one, although as a pre-generated effect, rather than calculated in real-time. One of the first modern music visualization programs was the open-source, multi-platform Cthugha (1994).

Subsequently, computer music visualization became widespread in the mid to late 1990s as applications such as Winamp (1997), Audion (1999), and SoundJam (2000). By 1999, there were several dozen freeware non-trivial music visualizers in distribution.

In particular, MilkDrop by Ryan Geiss, G-Force by Andy O’Meara, and Advanced Visualization Studio (AVS) by Nullsoft became popular music visualizations. AVS is part of Winamp and has been recently open-sourced, and G-Force was licensed for use in iTunes and Windows Media Centerand is presently the

flagship product for Andy O’Meara’s software startup company, SoundSpectrum. The real distinction between music visualization programs such as Geiss’ MilkDrop and other forms of music visualization such as music videos or a laser lighting display is a visualization program’s ability to create different visualizations for each song every time the program is run.

 

3 Steps

  • 1. Converting sound to frequency spectrum
  • 2. Converting frequency spectrum to images
  • 3. Converting images/ photos back to sound

 

 Introduction to Audio Frequency, Spectrogram and FFT 

An audio frequency is characterized as a periodic vibration whose frequency is audible to the average human. It is the property of sound that most determines pitch and is measured in hertz (Hz). The generally accepted standard range of audible frequencies is 20 to 20,000 Hz, although the range of frequencies individuals hear is greatly influenced by environmental factors. Frequencies below 20 Hz are generally felt rather than heard, assuming the amplitude of the vibration is great enough. Frequencies above 20,000 Hz can sometimes be sensed by young people. High frequencies are the first to be affected by hearing loss due to age and/or prolonged exposure to very loud noises.

A spectrogram, or sonogram, is a visual representation of the spectrum of frequencies in a sound or other signal as they vary with time or some other variable. Spectrograms are sometimes called spectral waterfalls, voiceprints, or voice grams. Spectrograms can be used to identify spoken words phonetically, and to analyze the various calls of animals. They are used extensively in the development of the fields of music, sonar, radar, and speech processing, seismology, etc. The instrument that generates a spectrogram is called a spectrograph. The sample outputs on the right show a select block of frequencies going up the vertical axis, and time on the horizontal axis.

A fast Fourier transform (FFT) is an algorithm to compute the discrete Fourier transform (DFT) and its inverse. A Fourier transform converts time (or space) to frequency and vice versa; an FFT rapidly computes such transformations. As a result, fast Fourier transforms are widely used for many applications in engineering, science, and mathematics. The basic ideas were popularized in 1965, but some FFTs had been previously known as early as 1805. Fast Fourier transforms have been described as “the most important numerical algorithm[s] of our lifetime.

 

observed_spectrum

 

3D-SPectrum-of-Sound

3D Spectrum of Sound

 

Step 1. Converting sound to frequency spectrum 

We can achieve this step by utilizing many existing spectrum analyzers.

A spectrum analyzer measures the magnitude of an input signal versus frequency within the full frequency range of the instrument. The primary use is to measure the power of the spectrum of known and unknown signals. The input signal a spectrum analyzer measures is electrical, however, spectral compositions of other signals, such as acoustic pressure waves and optical light waves, can be considered through the use of an appropriate transducer. Optical spectrum analyzers also exist, which use direct optical techniques such as a monochromator to make measurements.

Screen Shot 2013-12-02 at 5.59.36 AM  Screen Shot 2013-12-02 at 5.59.46 AM

 

Step 2. Converting frequency spectrum to images

The minim library in Processing contains a lot of examples that could convert the sound frequency and related format of frequency, such as DDT and FFT into images.

Screen Shot 2013-12-02 at 5.58.27 AM

 

Step 3. Converting images/ photos back to sound

http://petapixel.com/2012/06/10/sounds-of-the-americans-converting-iconic-images-into-sound-and-back-again/

Project- Converting Images into Sound

 

How it works?

A video introduces how to convert sound into images step by step

 

References & Links

http://www.perlmonks.org/?node_id=1016588

http://petapixel.com/2012/06/10/sounds-of-the-americans-converting-iconic-images-into-sound-and-back-again/

uisoftware.com/metasynth

http://petapixel.com/2012/06/10/sounds-of-the-americans-converting-iconic-images-into-sound-and-back-again/

http://en.wikipedia.org/wiki/SoundSpectrum

http://en.wikipedia.org/wiki/Music_visualization

http://en.wikipedia.org/wiki/Real_Time_Analyzer

GRID multi-touch sound visualization : https://vimeo.com/26226875

Processing work of sound visualization : https://vimeo.com/58704425

http://www.codeproject.com/Articles/488655/Visualizing-Sound

https://itunes.apple.com/ca/app/spectrum-analyzer/id490078884?mt=8

http://www.howtogeek.com/96690/stupid-geek-tricks-how-to-turn-images-and-photos-into-sound-files/

http://www.perlmonks.org/?node_id=1016588

 

 

 

ADVERTISING INNOVATION

Advertising Innovation

Digital technology apply in Out of Home Advertising (OOH) Industry

Abstract

Technology is bringing about a change in our advertising choices and the media mix that evolves. Marketers need to be knowledgeable on the latest and greatest in the world of Digital Innovation. There are many ways to get the technologies into an advertising to give deeper impression into customers. At the same time, new technologies can also create different advertising effect and interactive-functions which are impossible realized in traditional advertising formats embedded the brand concept or the product sell point into an advertising. This research describes the simple history of advertising and the current formats of advertising based on technology developments, and it demonstrates the OOH potentials in current market by analysis the data of an OAAA report on advertising markets and an OOH project. It also describes the advantages of the OOH especial in new technology applied OOH. At the end, there are seven cases of digital OOH which are applied with SCM, video detection, shape match and shape recognize technologize. These technologize which describes different ways to use these technologies to improve the effect of advertising concept connect with social network, real word, and game world. These cases indicates the future directions of digital OOH.

DOCUMENT :

ADVERTISING INNOVATION 

REPORT:

 ADVERTISING INNOVATION REPORT PPT

Research Report – Children’s Toys and Microcontrollers

Children’s Toys and Microcontrollers

Arduino

(link to the presentation given in class)

I was introduced to the Arduino and the concept of micro-controllers in the Creation and Computation class. When I first took it out of the box I had no idea what it was and what it was capable of. As time rolled by I was taken back to the year 1987 when I first used the BBC Microcomputer in secondary school. For its time, the BBC Micro was revolutionary. A precursor to the Arduino, the BBC Micro due to the very nature of its being helped spark off a generation of garage software & game developers who later went on to become influential players in the software & app business. Co-relating this to the Arduino and the resulting Maker revolution, I saw a pattern emerge and decided to do my research report on both the BBC Micro and the Arduino and perhaps even how the Arduino may have a much longer life and impact than the BBC Micro.

 

Of micros and acorns

 

250px-Bbc1globe1978large 

627883acorn-computers.logo

The year is 1981 and the British Broadcasting Corporation (BBC) is all set to launch a massive computer literacy project that included a TV show “The Computer Programme” and the production of an accompanying machine called the “BBC MICRO” developed by ACORN for the BBC 

 

 

 

bbc-micro-logo

 

 

 

 

Born: 1981

Place: United Kingdom

Creators: BBC & Acorn

Price: The 32 bit RAM MICRO was priced at £399

Units sold: Acorn expected to sell 12,000 units and ended up selling a whopping 1.5 million units worldwide

Purpose: The purpose of the MICRO was not just programming but also graphics, controlling peripheral devices, sound & vision and Artificial Intelligence

bbc_micro_large1

What it did: The BBC Computer Literacy Project became one of the most successful computer literacy projects in history

BBC Micro was an excellent tool to introduce young people to programming

The widespread availability of BBC BASIC led to the creation of a cottage industry to provide software for the computer

Many of the ‘companies’ that were formed were started by young people who would later go on to establish the UK gaming industry as the third strongest in the world

 

_46504129_bbc_micro4922688433_01c272bc35_obbcBBC-Micro-boot-xoombbc micro

 

Below is a first person account representing the generation of programmers that the BBC Micro created, for more examples please check the presentation link.

“I started coding games at home when I was 11 years old”

“There was an explosion of creativity, most of it coming from self-taught young men like us working at home”

_57049319_darlingDavid Darling CBE is the co-founder of Codemasters

and now runs Kwalee, a smartphone game developer

 

 

 

 

arduino-danielandrade-net-83273

Born: 2005

Place: Interaction Design Institute at Ivrea, Italy

Creators: Massimo Banzi, David Cuartielles, David Mellis

Origin of the name: Inspired by a bar in Italy “Bar Di Re Arduino”, originally a boys name in Italian meaning “brave friend”

Price: $30

Units sold: Approx 250,000

Purpose: Arduino is an open-source electronics prototyping platform based on flexible, easy-to-use hardware and software. It’s intended for artists, designers, hobbyists, and anyone interested in creating interactive objects or environments

What its doing:

 

Applications:

Applications

Hackerlings:

A 12-Year-Old’s Quest To Remake Education, One Arduino At A Time

Twelve-year-old electronics prodigy Quin Etnyre wanted to make education more fun. So he became a teacher.

Fart_sensor_02

Quin Etnyre

Age 12

Inventor

A shining star in the next generation of “makers”. Enjoyed soldering circuit boards at Maker Faire Bay Area and started ordering components online and taught himself how to code. Teaches Arduino coding and programming. Launched his company Qtechknow in 2012. Struck a deal with SparkFun which now sells his product the “Qtechknow ArduSensors Kit” with tutorials written by Quin

Inventions:

PSC0913_DY_051FUZZ BOT: Quin started with a robot chassis kit for Arduino that he received last Christmas. “And then one morning, I decided to hook up a Parallax Ping sensor so that it could avoid obstacles,” he says. “From then on, I worked on the code and perfected it.” Quin also added extra functionality; the FuzzBot can clean floors. Now he’s working on a wireless controller

QUINQuin also developed the “Gas Cap”or what he likes to call “a fart sensor”.  A cap with LEDs that blinks when it detects Methane

 

Sylvia Todd

Age 12

Inventor

24sylvia-span-articleLarge PSC0913_DY_046

Has her own YouTube Channel “Super Awesome Mini Maker Show” which has over 1.5 million views views with over 20 episodes featuring beginner level projects for kids

Her projects have included a pendant that measures your heartbeat & waterColorBot; a robot that paints with watercolors

 

 

Arduino for Disabilities

In July 2011, 5 Art & Design students from the University of Arts in Philadelphia were paired with 5 people with disabilities in an attempt at collaborative design

mitchellchristine p1010958_sm p1020004_sm1 p1010977_sm_cropped p1010932_sm_cropped2

The purpose was to explore how micro-controllers can empower people with disabilities

a-measuring j-servoaction_sm x-p1010470_sm

Michael loves photography.

A knee-actuated switch (so Michael can steer the wheelchair with his hands) allows him to take photographs when a servomotor is activated within the mount and clicks for him while he is on the move

 

Can Google play the role of the BBC?

Google chairman Eric Schmidt announced that Google would help pay for 100 new science teachers and equip classrooms with Arduino kits and Raspberry Pi microcomputers.

111207012141-eric-schmidt-google-story-top

“The success of the BBC Micro in the 1980s shows what’s possible. There’s no reason why Raspberry Pi shouldn’t have the same impact, with the right support”

 

Inference:

My Arduino and I are a part of a revolution. What propelled the Micro to stardom also sealed its fate. The BBCs ultimate incapacity to look beyond the Micro as an accessory for the TV program resulted in its demise. The Arduino being an open-source hardware with an ever-growing community promises a phenomenal evolutionary path where the micro-controller will keep growing. The community openly share their creation(s) and provide support. With such dynamics the Arduino is bound to outlive the Micro.

Bibliography

 

The BBC Microcomputer and me, 30 years down the line. (2011, January 12). BBC News.

Retrieved November 30, 2013, from http://www.bbc.co.uk/news/technology-15969065

 

Arduino – HomePage. (n.d.). <i>Arduino – HomePage</i>.

Retrieved November 30, 2013, from http://arduino.cc

 

A 12-Year-Old’s Quest To Remake Education, One Arduino At A Time. (n.d.). <i>Popular Science</i>.

Retrieved November 27, 2013, from http://www.popsci.com/technology/article/2013-08/short-circuit

 

Arduino For Disabilities. (n.d.). Arduino For Disabilities.

Retrieved November 30, 2013, from http://arduinofordisabilities.wordpress.com

 

BBC Micro. (n.d.). computinghistory.org.

Retrieved November 30, 2013, from http://www.computinghistory.org.uk/cgi/archivehttp://www.computinghistory.or

 

Calling All Teachers. (n.d.). Quarkstream.

Retrieved November 30, 2013, from http://quarkstream.wordpress.com/calling-all-teachers/g.uk/cgi/archive

 

Open Source Hardware Association. (n.d.). Open Source Hardware Association.

Retrieved November 30, 2013, from http://www.oshwa.org/research/brief-history-of-open-source-hardware-organizations-and-definitions/

 

The BBC Micro. (n.d.). CHM Blog The BBC Micro Comments.

Retrieved November 30, 2013, from http://www.computerhistory.org/atchm/the-bbc-micro/

 

geekosystem. (n.d.). Geekosystem Google to Put Arduino Raspberry Pi Computers in UK Classrooms Comments.

Retrieved November 30, 2013, from http://www.geekosystem.com/google-raspberry-pi-uk/