iot and big data - the perfect marriage
TRANSCRIPT
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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
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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
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How Big is the IOT Market?
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HOW IS IT DIFFERENT FROM M2M?
THE CURRENT ERA OF IOT
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CHANGE IN BUSINESS MODEL
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[Source: http://postscapes.com/what-exactly-is-the-internet-of-things-infographic ]
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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 Disconnected Connected World
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FUTURE OF COMMUNICATIONS AND PRODUCTIVITY
BRING IOT TO THE NEXT LEVEL
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Improved Performance
Reduced Costs
Create Innovative Products
New Revenue Streams
Monitor
Autonomous
Optimize
Control
BUSINESS OPPORTUNITIES Capabilities Benefits
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Security and Privacy of data
Managing vast amounts of data
Fragmented industry
Finding the right business model
WHAT ARE THE BUSINESS CHALLENGES
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WHY TELCOS HAVE DIFFICULTY TO EMBRACE IOT
4 REASONS
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LEGACY BUSINESS IS STILL CONNECTIVITY
M2M HIGH VOLUME LOW ARPU
SIM-CARD BASED
OLD HABITS DIE HARD
LESS COMPLEX
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LACK OF DOMAIN EXPERTISE
THINK BEYOND CONNECTIVITY
SOLUTIONS, SELLING AND MANAGED SERVICES
NEED GO-TO-MARKET PARTNER
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MINDSET BLOCK
FULL OF SKEPTISM
LOW SINGLE DIGIT GROWTH CONTRIBUTION
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STABLE BUSINESS VS. RISKY VENTURES
NEED TO WORK LIKE STARTUP
IOT BUSINESS IS FLUID
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END-TO-END IOT SERVICE PROVIDER
THE END GAME
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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
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CONNECTIVITY PLAYER PHASE-1
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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
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IOT ENABLER PLAYER PHASE-2
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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
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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
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IOT SOLUTIONS PLAYER PHASE-3
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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
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IOT SERVICE PROVIDER PHASE-4
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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
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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
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MAKING SENSE OF SENSOR DATA … BUT WHAT DATA?
THE GOLD RUSH
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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
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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
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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
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Home Health Transport Office Waste
DATA BLENDING
Creating New Compound Applications
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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
Public Private
[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
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ENCOURAGE ADOPTION AND INNOVATION OF IOT
HOW-TO
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“Makers, startups and crowdsourcing efforts result in high numbers of low-revenue niche IoT applications.”
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WHERE ARE THE IOT DEVELOPERS?
[Source: http://arc.applause.com/2015/07/27/internet-of-things-big-data-and-analytics/]
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SENSING-AS-A-SERVICE WHAT-IF
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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
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HARNESSING THE CREATIVITY
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PARTICIPATORY SENSING – “RAPID DEPLOYMENT”
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REDUCTION OF DATA ACQUISITION COST – “SUSTAINABLE BUSINESS MODEL”
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DIFFERENT BUSINESS MODELS
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COLLECT DATA PREVIOUSLY UNAVAILABLE – “ASSIST SCIENTIFIC OR SURVEY ACTIVITIES”
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CROWDSENSING GETTING INSIGHTS FROM
EMPOWER THE CITIZENS TO SENSE
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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)
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MAKING CITIES BETTER USING CITIZENS
Traffic
Noise Environment
Network Coverage (WiFi/3G/4G)
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LET ALL CITIZENS BE OUR “EYES”
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Incident reporting facilities - citizens can report on issues concerning public infrastructure allowing collective collaboration to ensure an active response
COLLECTIVE COLLABORATION WITH CITIZENS
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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
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WHICH CAME FIRST – THE CHICKEN OR THE EGG?
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SMART CITIZENS AND SENSORS CONNECTING AND AGGREGATING
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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
Copyright©RIOT2015AllRightsReserved[Source: http://inrix.com]
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IOT AND BIG DATA MARRIAGE CHALLENGES
IOT DEMAND A NEW WAY THINKING
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CHALLENGE #1
FLOOD MONITORING
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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?
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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
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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.
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CHALLENGE #2
RIVER MONITORING
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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?
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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
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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
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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?
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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.
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THANK YOU @REDtoneIOT REDtoneIOT