IOT and Big Data - The Perfect Marriage

Copyright © RIOT 2015 All Rights Reserved
INTERNET OF THINGS & BIG DATA
THE PERFECT MARRIAGE
Dr. Mazlan Abbas
CEO, REDtone IOT Sdn Bhd
International Conference on Soft Computing in Data Science 2015 (SCDS2015), 2-3 Sept. 2015, Pullman, Putrajaya

THE PERFECT MARRIAGE
•  Introduction - Internet of
Things and its Business
Opportunities
•  Making Sense of Data
•  Encourage Adoption and
Innovation of IoT
•  IOT and Big Data Marriage
Challenges
•  Summary

How Big is the IOT Market?

HOW IS IT DIFFERENT FROM
M2M? 

THE CURRENT ERA OF IOT

CHANGE IN BUSINESS MODEL

[Source:
http://postscapes.com/what-exactly-is-
the-internet-of-things-infographic ]

10/90 RULE
The Last 100 meter
connectivity
The “last 100 meters” represent > 90% potential number of connections
Today, the devices used in the “last 100 meters” are typically not connected. The wide-area network is
to a larger extent connected e.g. through smartphones, home routers (e.g. ADSL routers) and GSM /
3G / 4G Routers.
Still DisconnectedConnected World

FUTURE OF COMMUNICATIONS
AND PRODUCTIVITY 

BRING IOT TO THE NEXT LEVEL

Improved
Performance
Reduced
Costs
Create
Innovative
Products
New Revenue
Streams
Monitor
Autonomous
Optimize
Control
BUSINESS OPPORTUNITIES
Capabilities Benefits

Security and Privacy of
data
Managing vast
amounts of data
Fragmented industry
Finding the right
business model
WHAT ARE THE BUSINESS CHALLENGES

WHY TELCOS HAVE DIFFICULTY
TO EMBRACE IOT
4 REASONS

LEGACY BUSINESS IS STILL CONNECTIVITY
M2M HIGH VOLUME LOW ARPU
SIM-CARD BASED
OLD HABITS DIE HARD
LESS COMPLEX

LACK OF DOMAIN EXPERTISE
THINK BEYOND CONNECTIVITY
SOLUTIONS, SELLING
AND MANAGED SERVICES
NEED GO-TO-MARKET PARTNER

MINDSET BLOCK
FULL OF SKEPTISM
LOW SINGLE DIGIT GROWTH
CONTRIBUTION

STABLE BUSINESS VS. RISKY VENTURES
NEED TO WORK
LIKE STARTUP
IOT BUSINESS IS FLUID

END-TO-END IOT SERVICE
PROVIDER
THE END GAME

s m a r t c i t y
smart transport
s m a r t
a u t o m o t i v e
END-TO-END IOT SERVICE PROVIDER
Device
Provider
Network
Provider
Platform
Provider
Application
Provider
Customer
Network
Platform

CONNECTIVITY PLAYER
PHASE-1

s m a r t c i t y
smart transport
s m a r t
a u t o m o t i v e
BUSINESS MODEL
Device
Provider
Network
Provider
Platform
Provider
Application
Provider
Customer
Network
Platform
Platform
1

IOT ENABLER PLAYER
PHASE-2

s m a r t c i t y
smart transport
s m a r t
a u t o m o t i v e
BUSINESS MODEL
Device
Provider
Network
Provider
Platform
Provider
Application
Provider
Customer
Network
Platform
2

s m a r t c i t y
smart transport
s m a r t
a u t o m o t i v e
BUSINESS MODEL
Device
Provider
Network
Provider
Platform
Provider
Application
Provider
Customer
Network
Platform
IOT
Subsidiary
3

IOT SOLUTIONS PLAYER
PHASE-3

s m a r t c i t y
smart transport
s m a r t
a u t o m o t i v e
BUSINESS MODEL
Device
Provider
Network
Provider
Platform
Provider
Application
Provider
Customer
Network
Platform
4

IOT SERVICE PROVIDER
PHASE-4

s m a r t c i t y
smart transport
s m a r t
a u t o m o t i v e
BUSINESS MODEL
Device
Provider
Network
Provider
Platform
Provider
Application
Provider
Customer
Network
Platform
5

s m a r t c i t y
smart transport
s m a r t
a u t o m o t i v e
BUSINESS MODEL -HYBRID
Device
Provider
Network
Provider
Platform
Provider
Application
Provider
Customer
Network
Platform
6

MAKING SENSE OF SENSOR
DATA … BUT WHAT DATA?
THE GOLD RUSH

TO OVERCOME 3 KEY CHALLENGES
Only by addressing all three can organizations turn raw data into information
and actionable insights.
Integrating data
from multiple
sources
Automating the
collection of data
Analyzing data to
effectively identify
actionable insights

Wisdom
Knowledge
Information
Data
More
Important
Less
Important
Evaluated understanding
Appreciation of
Answers to questions.
Symbols
Understanding
Answers to
questions
WHO
WHY
HOW
WHAT
WHERE WHEN
VALUE IS CREATED BY MAKING SENSE OF DATA
VALUE PYRAMID

Wisdom
Knowledge
Information
Data
More
Important
Less
Important
N/A
Empty (0), Full (1)
Understanding
EXAMPLE SMART PARKING
Who park at this lot?
What kind of vehicle?
Where is the empty parking lot?
When is the peak period?
How to implement a tiered charging?
How to find “overstayed” vehicles?
Why this parking area is not fully
occupied?
Who Benefits? - Citizens / Parking Operators / City Council / Shops

Home Health Transport OfficeWaste
DATA BLENDING
Creating New Compound Applications

All personal items, such as mobile phones,
wrist watches, spectacles, laptops, soft
drinks, food items and household items,
such as televisions, cameras, microwaves,
washing machines, etc
Private business
organization has the right
to take the decision
whether to publish the
sensors attached to those
items to the cloud or not.
Public infrastructure such as
bridges, roads, parks, etc. All
the sensors deployed by the
government will be
published in the cloud
depending on government
policies.
Business entities who deploy
and manage sensors by
themselves by keeping
ownership. They earn by
publishing the sensors and
sensor data they own
through sensor publishers.
Personal and Households
Commercial
Sensor Data
Providers
Organizations
PublicPrivate
[Source: “Sensing as a Service Model for Smart Cities Supported by Internet of Things”, Charith Perera et. al., Transactions on Emerging
Telecommunications Technology, 2014]
CHALLENGES – DATA OWNERSHIP

ENCOURAGE ADOPTION AND
INNOVATION OF IOT 

HOW-TO

“Makers, startups and crowdsourcing efforts result in
high numbers of low-revenue niche IoT applications.”

WHERE ARE THE IOT DEVELOPERS?
[Source: http://arc.applause.com/2015/07/27/internet-of-things-big-data-and-analytics/]

SENSING-AS-A-SERVICE
WHAT-IF

The city would pay for access to
the light sensors in order to
decide when to turn on and off
the street lights
Gathering temperature, light,
pressure, humidity and
pollution.
COMMERCIAL IOT SENSOR PROVIDER
A university may want access
to the pollution information for
research purposes for a limited
period
The weather department
would want the temperature
and pressure data
The street town council center
would want the temperature
and humidity data for
planning during rough
weather

HARNESSING THE CREATIVITY

PARTICIPATORY SENSING – “RAPID DEPLOYMENT”

REDUCTION OF DATA ACQUISITION COST –
“SUSTAINABLE BUSINESS MODEL”

DIFFERENT BUSINESS MODELS

COLLECT DATA PREVIOUSLY UNAVAILABLE –
“ASSIST SCIENTIFIC OR SURVEY ACTIVITIES”

CROWDSENSING
GETTING INSIGHTS FROM
EMPOWER THE CITIZENS TO
SENSE

SMARTPHONE AS YOUR “SENSING ASSISTANT”
Sensors:
①  Camera – “Eyes”
②  Audio – “Ears”
③  Accelerometer –
“Speed”
④  GPS – “Location”
⑤  Gyroscope –
“Movement”
⑥  Compass – “Direction”
⑦  Proximity –
“Closeness”
⑧  Ambient light – “Eyes”
⑨  Others…
Crowdsourcing Via Crowdsensing
Context
①  Spatial – Location / Speed Orientation
②  Temporal – Time / Duration
③  Environmental – Temperature / Light / Noise Level
④  User Characterization – Activity (Mobility Pattern) / Social (Friends, Interactions)

MAKING CITIES BETTER USING CITIZENS
Traffic
NoiseEnvironment
Network Coverage
(WiFi/3G/4G)

LET ALL CITIZENS BE OUR “EYES”

Incident reporting facilities - citizens can report on issues concerning public infrastructure allowing
collective collaboration to ensure an active response
COLLECTIVE COLLABORATION WITH CITIZENS

MOBILE
APPLICATION
LIVABILITY LOCAL AREA
SERVICES
PUBLIC SAFETY NATURAL DISASTER
Open Data
Smartphone Users
Social Media
Users
PORTAL
CITISENSE.COM
CASE MANAGEMENT
SYSTEM
DASHBOARD
EMPOWERING SMART CITIZENS

WHICH CAME FIRST – THE CHICKEN OR THE EGG?

SMART CITIZENS AND SENSORS
CONNECTING AND AGGREGATING

Smart
City
Environmental
Monitoring
Multiple Sensors
Outdoor Parking
Management
Parking sensors
Mobile
Environmental
Monitoring
Sensors installed in
public vehicles
Traffic Intensity
Monitoring
Devices located at
main entrance of
city
Guidance to free
parking lots
Panels located at
intersections
Smart Citizen
Crowdsensing
Parks and Gardens
Irrigation
Sensors in green zones
•  Temperature
•  CO
•  Noise
•  Car Presence
•  Ferromagnetic
sensors
•  Temperature
•  CO
•  Noise
•  Car
Presence
•  Measure main traffic parameters
•  Traffic volumes
•  Road occupancy
•  Vehicle speed
•  Queue Length
•  Taking information retrieved by the
deployed parking sensors in order to
guide drivers towards the available
free parking lots
•  Moisture temperature
•  Humidity
•  Pluviometer (rain gauge)
•  Anemometer (wind-speed)
•  User generated feedback
with smartphones that help
to make cities better

[Source: http://inrix.com]

IOT AND BIG DATA MARRIAGE
CHALLENGES
IOT DEMAND A NEW WAY THINKING

CHALLENGE #1
FLOOD MONITORING

PREDICTING FLOOD
1.  What is the water level in the river?
2.  When does the river swell up?
3.  Where is the location of water rise?
4.  Where are the areas that require immediate evacuation?
5.  Who is contributing to the rise in water level?
6.  How to control the water level?
7.  How fast is the water rising?
8.  Why is the water rising?

FLOOD – DIFFERENT SENSORS
1.  Water level and weather sensors
2.  Tide monitoring sensor
3.  Astronomical data
4.  GPS for rescue vehicles (Plug-n-Play OBD)
5.  GIS data
6.  Camera
7.  Social network integration

FLOOD MONITORING – VALUE PROPOSITION
1.  Early warning system for floods
2.  Locating the area of violation (cause of floods)
3.  Efficient rescue planning
4.  Plan the widening of the river banks
5.  Plan deepening of the river bed
6.  Predict the conditions of flooding when coupled with a weather
station, astronomical, tide and GIS.

CHALLENGE #2
RIVER MONITORING

MONITORING RIVER POLLUTION
1.  What are the pollutants in the river?
2.  What is the pollution level?
3.  When is the highest pollution detected?
4.  Where is the location of pollutants?
5.  Who is contributing to the rise in pollution?
6.  How to control the pollution level?
7.  How much is the pollution level?
8.  Why is the pollution rising at certain time?
9.  Why is the pollution rising at certain locations?

RIVER MONITORING - SENSORS
1.  Chemical sensors
2.  Water level sensors
3.  Crowd sourced violation information (mobile device)
4.  GPS input
5.  Hydro morphology e.g. depth, width, flow
6.  Water temperature sensor
7.  In-situ (manual sampling)
8.  Weather sensors

RIVER MONITORING – VALUE PROPOSITION
1.  Early warning system for water contamination
2.  Locating the area of violation
3.  Detecting and alerting violations
4.  Getting public involvement through crowd sourcing
5.  Evidence platform for violations
6.  Identify potential causes of pollution rise by correlating data with
water level pattern
7.  Identify a profile of water in different months of the year. Any
change in profile will trigger external sources of pollution
8.  Identify the spread of disease
9.  Ecotourism planning

Tons of
interesting data
If you can’t take action on the
data being collected, it’s likely not
worth collecting, storing and
analyzing.
Is it actionable for
my business?

The Internet of Things and Big Data are two sides
of the same coin, and building one without
considering the other is a recipe for doom.

THANK YOU
@REDtoneIOTREDtoneIOT

IOT and Big Data - The Perfect Marriage

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