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Small Sensors. Big Data.
Prof. Barry Smyth Insight Centre for Data Analytics University College Dublin !e: barry.smyth@insight-centre.org t: @barrysmyth
Data, data, everywhere…
1 = 10bytes18exabyte
1 = 10bytes18exabyte
1000,000,000,000,000,000
1 = 10bytes18exabyte
20,000 x all of the printed material in the
US Library of Congress. Or all of the words spoken by humans. Ever!
1 = 10bytes18exabyte
6 !hours
But, we now create this much information every
A PARADIGM SHIFT
algorithm !
data
algorithm !
data
computation
sensorsdev
data
THE WORLD’S FIRST SUPERCOMPUTER
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, $60m
MOORE’S MAGICAL LAWS
A SELF-FULFILLING PROPHECY?
CDC 6600
[1964]
IBMPC [1981]
iPHONE 5S [2013]
0.05FLOPs/$
200FLOPs/$
8MFLOPs/$
x4,000 x40,000
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 than to park it downtown for an evening.” (Carver Mead)
THE RISE OF THE SENSOR WEB
UNIVERSAL MOBILE SENSING PLATFORM
UNIVERSAL MOBILE SENSING PLATFORM
C A M E R A
M ICROPHONES 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
L OCATION
TOUCH
MOTION
DIRECT IONF I N G E R P R I N T S
Connectivity high-speed data
Mobility location-aware
Power always on
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’S AN APP FOR 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 Analytics
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
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.
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 ON MOBILE SENSING
SCALING
vertical scaling
horizontal scaling
horizontal scaling
PARTICIPATORYSENSING
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, ...
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 to them.
FROM REAL TO VIRTUAL SENSORS
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.
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
82M Queries
6M Users
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 verified CDC data.
MINING USER-GENERATED REVIEWS
USER-GENERATED REVIEWS
+‘ves staff
location bed
service breakfast
-‘ves noise elevators carpet health club public transport
Chicago Hotels
OPINION AMPLIFICATION
Twitter, FaceBook as a source of real-time opinions. !
Raw Text ⇒ Sentiment ⇒ Opinion !
These days Twitter data has been used to predict election outcomes, box office success, and musical talent ...
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
The Big Data Revolution is here today! !
Transformation ⇒ Disruption ⇒ Opportunity !
People as Sensors ⇒ Collective Intelligence !
Personal Data, Privacy, Ethics …
SMALL SENSORS. BIG DATA. FROM CLARITY TO INSIGHT IN THE WORLD OF THE SENSOR WEB
Creating a Data-Driven Society
Small Sensors. Big Data.
Prof. Barry Smyth Insight Centre for Data Analytics University College Dublin !e: barry.smyth@insight-centre.org t: @barrysmyth
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