Small sensors-big-data-barry-smyth-ria-2013

SMALL SENSORS. BIG DATA.FROM CLARITY TO INSIGHT IN THE WORLD OF THE SENSOR WEB

Barry Smyth, INSIGHT Centre for Data Analytics@barrysmyth, barry.smyth@ucd.ie

Tuesday 1 October 13

In a typical lifetime ...

1 billion breaths 2.5 billion heart beats 100 million litres oxygen 100 trillion cells 50,000 litres water 70 tonnes food 70 million calories 3 years toilet 1 billion km 1 year traffic 50,000 kms walking 0.5 million kWh 250 tonnes coal 50 tonnes waste 12 years work 500 days sick 150,000 yawns 28 years asleep 2 years reading 9 years of TV

1 = 10bytes18exabyte

1000,000,000,000,000,000

20,000 x all of the printed material in the

US Library of Congress.Or all of the words spoken by humans. Ever!

6 !hours

But, we now create this much information every

Connecting atoms & bits.

From algorithms to data.

A PARADIGMSHIFT

algorithmdata

algorithm

dataTuesday 1 October 13

VSIT’S NOT (JUST) ABOUT THE DATA

N = all

Messy & Diverse

Reusable

Correlation

N = small

Clean & Uniform

Disposable

Causation

computation

sensorsdev

THE WORLD’S FIRSTSUPERCOMPUTER

Brainchild of Seymour Cray, in 1964 the closet-sized CDC 6600 was the biggest, baddest computer of the age.

5,500 kgs, 480 kb RAM, 3M FLOPs, $60m

MOORE’S MAGICAL LAWS

In 1965, Intel co-founder, Gordon Moore, noted a doubling of “computing power” every 1-2 years and predicted that this would continue for at least 10 years...

... this became known as Moore’s Law.

A SELF-FULFILLING PROPHECY?

CDC 6600

[1964]

IBMPC[1981]

iPHONE 5S[2013]

0.05FLOPs/$

200FLOPs/$

8MFLOPs/$

x4,000 x40,000

TO PUT THIS INTO PERSPECTIVE ...

The iPhone 5S is about 60,000 times more powerful that the Apollo 11’s guidance computer.

IF MOORE’S LAW APPLIED TO CARS?

“If the auto industry had moved at the same speed ... ...your car today would cruise comfortably at a million miles an hour and probably get a half a million miles per gallon of gasoline. But it would be cheaper to throw your Rolls Royce away

RAYKURZWEIL

“A computer that once fit in a building, when I was a student, now fits in my pocket and is one thousand times more powerful despite being a million times less expensive.”

MEMORY, DISK SIZE, BANDWIDTH, PIXELS,...

All subject to Moore’s Law like improvements over the past 30 years...

... except for battery power / energy density.

THE RISE OF THESENSORWEB

UBIQUITOUS COMPUTING

Mark Weiser’s 1988 vision for a Post-PC world saw computing evolve from a terminal-based paradigm to one in which computing and computation would simply disappear into the fabric of our world.

Tabs, Pads, Boards ⇒ Smart Dust, the Internet of Things, Wearable Computing

THE EMERGINGSENSOR WEB

Boards

Smart Sensors

The Internet of Things

Wearable Computing

A MATERIALS SCIENCE DETOUR

Chemistry & Physics ⇒ Novel Materials & Structures

Common Materials ⇒ Next Generation Sensors

NOKIA’S MORPH CONCEPT DEVICE

CHALLENGES OF PHYSICAL SENSING

Conventional sensors (thermistors, flow meters, photoreceptors).

Biofouling & Calibration.

Robustness, Reliability, Energy & Communications.

Cost, Cost, Cost.

SWEATSENSING

Microfluidic, Lab-on-a-Chip, Wearable.

pH sensitive dye &photo-detector.

Accurate, continuous, realtime

Athletic performance ⇒ Cystic Fibrosis

UNIVERSAL MOBILE SENSING PLATFORM

C A M E R A

MICROPHONES P E E D

L I G H T

O R I E N T A T I O N

HUM IDITY

T E M P E R A T U R E

LOCATION

MOTION

DIRECTIONF I N G E R P R I N T S

Connectivityhigh-speed data

Mobilitylocation-aware

Poweralways on

THE QUANTIFIED SELF MOVEMENT

A data-rich approach to everyday living.

Gordon Bell (Microsoft) and the My Life Bits project ⇒ Digitizing everyday life.

SenseCam

7 YEARS3 MONTHS2 WEEKS 1 PERSON12M PHOTOS1TB

Activitiesclassificationsummarisation

Lifestylebehaviourspreferences

Eventssegmentation

clustering

THE DISRUPTION OF HEALTHCARE

Always-on personal sensing, 24/7/365

The Creative Disruption of Healthcare

Activity and exercise, sleep and moods, food, blood glucose, heart rate, pulse ox, lung function, ...

THERE’SAN APPFOR THAT

EXERCISE & FITNESS

Runkeeper iPhone/Android

Running, Walking, Biking, ...

Age, gender, weight, ...

Location, pace, duration, climb, calories, heart rate,...

TRACKING SLEEP

Basic ‘sleep tracking’based on motion.

Duration vs Movement

Sleep Quality (≈ time/move)

Sleep Notes / Wakeup Moods

Comparative AnalyticsTuesday 1 October 13

MOOD & FOCUS

The Melon Headband

Uses EEG to track brain activity to assess ‘focus’.

Tagging, location, and activity information helpsusers to better assess what impacts their focus.

FOOD & NUTRITION

Meal logging and nutritionalanalysis.

Manual vs Semi-Automatic.

Calorie goals and diet plans.

Integrated weight tracking.

HEART RATE SENSING

Using smartphone camera with your finger. No external sensor required.

Detecting colour changes due to capillary blood-flow.

Tagging, comparative analytics etc

BLOOD GLUCOSE

External blood glucose sensorautomatically syncs readings with app.

Readings tagged withmealtime, exercise etc.

Analysis and visualization of trends, logs, stats.

MOBILE SPIROMETRY

Using a mobile phone microphone to evaluate lung function.

FVC, FEV, PEF measures.

Audio ⇒ Features ⇒ Machine Learning.

Mean 5.1% error wrt clinical spirometry ⇒ suitable for home-based monitoring.

MOBILE SPIROMETRY

Using a mobile phone microphone to evaluate lung function.

FVC, FEV, PEF measures.

Audio ⇒ Features ⇒ Machine Learning.

Mean 5.1% error wrt clinical spirometry ⇒ suitable for home-based monitoring.

SENSORS& SPORTS

Profs Brian Caulfield & Niall Moyna (@ CLARITY)

Player Health vs Performance Analysis

Rugby, Athletics, Cycling, Equestrian, Archery, Boxing, GAA, ...

AUTOMATIC TACKLE CLASSIFICATION

GPS +Accelerometer

CONSUMER-DRIVEN HEALTHCARE?

Towards preventative, sensor-based, data-driven healthcare.

Sparse checkups ⇒ 24/7/365 Sensing

The data is ours to share ...

Apps vs Prescriptions?

ALWAYS ONMOBILESENSING

SCALINGTuesday 1 October 13

vertical scalingTuesday 1 October 13

horizontal scalingTuesday 1 October 13

PARTICIPATORYSENSINGTuesday 1 October 13

ASTHMOPOLIS SMART INHALER

PARTICIPATORY SENSING

HACKING YOUR COMMUTE

GPS & Navigation Assistants

Map Apps Rule the World

TomTom, Garmin, Google, Apple, Nokia, ...

CROWDSOURCED MAPPING (WAZE)

Free smartphone app.

Real-time sensing of users’location, time, speed etc.

x millions of users

= social mapping + traffic flow, alerts, hazards, ...

CITIZEN SENSING PUBLIC TRANSPORT

Roadify (iPhone App)

Status updates for publictransport experiences.

Train, bus, subway, ferry,parking, ...

Opinions ⇒ Alerts, Recommendations, Delays, ...

TURNING PEOPLE INTO SENSORS

Participatory/Citizen Sensing

Big, messy data ⇒ real-time insights.

The smartphone as a mobile sensor platform...

... and the willingness of people to contribute to data to causes that matter

FROM REALTO VIRTUALSENSORS

MINING THE DATA EXHAUST

From Real to Virtual Sensors

Page Views, Read Times, Mouse Movements, Search Queries, Result Clicks, Social Connections, Share, Comments, Likes, Posts, Emails, IMs, ...

THE ORIGINAL BIG DATA COMPANY

Mining relevance & reputation from links.

Search logs as sensor data.

PAGERANK GOOGLE’S BIG IDEA

The importance of a page as a ranking signal.

Estimating importance from in-links ...

... and PageRank was clever way to count in-links to

accurate estimate importance.

GOOGLE’S BIGGER IDEA

$40 billion

Google’s real Bigger Idea was that it’s search engine could sense our intentions through our queries and click ...

... and that it could match this demand with real-time supply through its search adverts.

SEARCH LOGS AS SENSOR DATA

“... Web search ... can be likened to a large-scale distributed network of sensors for identifying potential side effects of drugs. There is a potential public health benefit in listening to such signals, and integrating them with other sources of information.”

“Web-Scale Pharmacovigilance: Listening to Signals from the Crowd” J Am Med Inform Assoc. (2013)

SENSING DRUG SIDE-EFFECTS

82MQueries

6MUsers

SENSING FLU TRENDS

Identified trigger terms correlated we known past outbreaks. Tracked real-time occurrence of these terms, location by location to deliver accurate* regional outbreak maps that correlated well with verifiedCDC data.

TURNING BROWSERS INTO BUYERS

Understanding user preferences.

Making personalized suggestions.

itemsus

Correlations between the ratingspatterns of users denote user similarity ...

People like you have also liked ...

itemsus

Conversely correlations between the ratings patterns of items denote item similarity ...

If you liked X then you might like Y...

MINING USER-GENERATED REVIEWS

USER-GENERATED REVIEWS

+‘vesstaff

locationbed

servicebreakfast

-‘vesnoiseelevatorscarpethealth clubpublic transport

Chicago Hotels

OPINION AMPLIFICATION

Twitter, FaceBook as a source ofreal-time opinions.

Raw Text ⇒ Sentiment ⇒ Opinion

These days Twitter data has been used to predict election outcomes, box office success, and musical talent ...

Participatory sensing as collective intelligence

Human Intelligence + Brute-Force Computation

TOWARDS COLLECTIVE INTELLIGENCE

DEALING WITH EMAIL SPAM

Back in 2000 Yahoo had a problem ...

Bots registering free email accounts for the purpose of bulk spam.

How to recognise real people from the spambots?

Luis Von Ahn

Manuel Blum

Yahoo! Mail CAPTCHATuesday 1 October 13

250mCAPTCHASPER DAY

150kPERSON-HOURSPER DAY

7mPERSONHOURS

45CAPTCHADAYS!

What if we coulddo something more with all of this

‘CAPTCHA time’?

99.1%word-levelaccuracy

1.2bnCAPTCHASin year 1

440mwords

17mbooks

GAMES WITH A PURPOSE

In 2003 there were 9bn hours of solitaire played on PCs...

... and these days there are around 70m hours of FarmVille played every week!

It only took about 20m hours of human effort to build the Panama Canal!

FOLD.IT - MOLECULAR GAME PLAY

HOW WELL DOES IT ALL WORK?

In 2011, players of Foldit helped to decipher the crystal structure of the Mason-Pfizer monkey virus (M-PMV) retroviral protease, an AIDS-causing monkey virus.

Players “produced” an accurate 3D model of the enzyme in just 10 days! This structure had eluded scientists for some 15 years.

Khatib, F. et al. (2011). "Crystal structure of a monomeric retroviral protease solved by protein folding game players". Nature Structural & Molecular Biology 18 (10): 1175

BIG DATA OR BIG BROTHER?

THE END OF THE AGE OF PRIVACY?

“Technology is neither good nor bad, nor is it neutral”

Public by Default.

The Price of Free?

Ownership of Personal Data?

THE END OF ANONYMITY

The Case of AOL Searcher No. 4417749.

20M anonymized queries, 600k users as research data (AOL, 2006).

User No. 4417749 = 62 year old Thelma Arnold of Lilburn, Ga.

THE PANOPTICON STATE?

Zamyatin’s dystopian glass-walled future of government surveillance.

NSA Prism programme.

A shift in the data ownership model ⇒ a new asset class for personal data?

Owned by the individual ⇒ shared with services.

Cloud storage (e.g. DropBox) as a shareable repository of personal data...

CONTROLLING PERSONAL DATA

THE BIG DATA WORLD OF THE SENSOR WEB

N = ALLMESSYCORRELATION

THE OPTION-VALUE OF BIG DATADATA-DRIVEN EVERYTHINGPOWER TO THE PEOPLE

THE OPTION-VALUE OF BIG DATA

Reuse & Recycle

From Primary to Secondary Uses of Data

The Unintended Consequences of Data

DATA-DRIVEN EVERYTHING

Social Science, Linguistics, Anthropology, Cultural Studies, Journalism, Political Science, Humanities ...

All impacted by Big Data Thinking...

GOOGLE’S N-GRAM VIEWER

Acerbi A, Lampos V, Garnett P, Bentley RA (2013) The Expression of Emotions in 20th Century Books. PLoS ONE 8(3)

DATA-DRIVEN EVERYTHING

Michel J-P, Shen YK, Aiden AP, Veres A, Gray MK, et al. (2011) Quantitative analysis of culture using millions of digitized books. Science 331: 176–182

Lieberman E, Michel J-P, Jackson J, Tang T, Nowak MA (2007) Quantifying the evolutionary dynamics of language. Nature 449: 713–716

Richards, Daniel Rex. "The content of historical books as an indicator of past interest in environmental issues." Biodiversity and Conservation (2013): 1-9.

Lampos, Vasileios, et al. "Analysing Mood Patterns in the United Kingdom through Twitter Content." arXiv preprint arXiv:1304.5507 (2013).

POWER TO THE PEOPLE

Personal Data & Personal Analytics

People as Sensors in Participatory Sensing

Human Computation & Collective Intelligence

Creating a Data-Driven SocietyTuesday 1 October 13

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