internet of things (rusmart 2013, st. petersburg)

© 2013 IBM Corporation

Internet of Things: The foundational infrastructure for a smarter planet28 August 2013

IBM Institute for Business Value

Rob van den Dam, Global Telecommunications Industry Lead IBV



The emerging Internet of Things attracts many players

2 IBM Confidential



Smarter Planet is IBM’s #1 research focus

3

TSL China & Research Lab

(Beijing)

TSL North America (Austin, Texas)

Japan

(TokyoSatellite TSL)

TSL Israel & Research Lab

(Haifa Satellite TSL)

Research Lab(New Delhi)

TSL LATAM(Sao Paulo,Brazil Satellite TSL)

TSL Europe(La Gaude &

Montpellier, France)

TSL Russia(Moscow Satellite TSL)

South Africa(Johannesburg, Satellite TSL)

ASEAN(Kuala LumpurSatellite TSL)

TSL India (Bangalore Satellite TSL)

Worldclass

Partner

Ecosystem

Institute for Business

Value

Industry

Solutions Labs

Research

Labs

Web

Services

Centers of

Excellence

Internet of Things Smarter Cities

Almaden c

Big Data & Analytics

Storage Nanotech

Healthcare

Watson Semiconductors Systems Software &

Services Big Data &

Analytics

c

Dublin

Smarter Cities



Internet-of-Things (IoT) provides the foundational infrastructure for a smarter planet ….

4

Hyper-growth of instrumented devices for sensing the world

The infrastructure to connect the devices, manage the sensor data and devices, and enable intelligence at edge and in data center

Significant growth opportunities for end-to-end infrastructure and services

Multiple Sources: Intel, Ericsson, Gartner, etc.

Number of Connected Devices

2010

15 Billion

7 Billion

50 Billion

10

20

30

40

50

2015 2020

Why IoT is needed? (SERCQ)

Safety and reliability of physical infrastructure

Efficient asset utilization and management

Reduction of energy and resources

Comply with regulation

Quality of service and life



..and differs from the Web on many aspects

5

End Point Not necessary IP based, heterogeneous

devices, constraint resource, no human

engaged

IP based servers/PC/mobile devices,

resource rich, human engaged on

device

Geo-distribution Outside data center, unmanned area Data center centric, manned

Communication

Pattern

Uplink intensive, relative fixed access

pattern, burst means important event

Downlink intensive, flexible access

pattern

Data 10-100X volume of transactional system;

numeric & multimedia; 24*7 continuous data

streams; noisy sensor data

Human generated content, Text, XML

are popular;

QoS and

Reliability

Stringent if managing mission critical

physical infrastructure

Best effort

Cyber v.s.

Physical

Cyber & physical, influenced by physical

world behavior model

Cyber mainly



IBM works on a number of top challenges in Large Scale IoT systems

6

Internet of Things

Sensing

Data

Processing

ManagementEdge

Computing

Simulation &

Testing

Security

Scale

Behavior

model

Sense the

impossible

before

Higher

sensitivity

Distance

Power

Reliability

Throughput

Reverse workload

pattern

Space & Time

Scalable

Automated

Intelligent

Distributed

End-to-end security with insecure

components and environment

Resource constraint

Resource

constraint

runtime

Collaborative

intelligence

Communication



As an example: challenges in communications include spectrum, power and inference issues

7

SPECTRUM CRISIS

• Spectrum is SCARCE

• Fast grow traffic requires more spectrum

POWER

• Communication is power intensive

• No external power supply in certain domain

INTERFERENCE

• Spectrum sharing

• Large Machinery

223.525 224.650 230.525 231.650

150KHz150KHz

15 groups for UL 15 groups for DL

Frequency

MHz

Power

…... …...228.750

10 groups for single

direction mode

…...228.075

Existing spectrum allocation for smart grid application in China

Source: US FCC

Spectrum Environment in Shanghai

1) Multiple Interferences

2) Working with certain periods

3) Unknown signals existed in the same band

Large machinery in mines, oil fields, etc.

RF is the BIGGEST portion of energy consumption of wireless sensors

More frequent communication, more percentage, energy consumed by RF



These challenges are addressed by IBM’s wireless M2M Platform, based on IT-based software defined radio technology

8

ConsumptionTransmission Distribution Petrol/Chemical Pipe Airport

Data Center

Feeder Terminal Unit

Transformer Terminal Unit

Feeder Terminal Unit

Transformer Terminal Unit

3G/4G Wireless

Substation

3G/4G

Wireless

Substation

Monitoring

& ControlSimu

Communication

Server

Control Center

IoT Infrastructure

Management & Operation

Command Center

SDH/SONET

RS232/ETH

IoT Infrastructure Manager

IoT Access Appliance

IoT Edge Appliance

Technical Features

• E2E SDR technology for high flexibility

• Optimized WiMAX-EXT for stable wireless communication

• Optimization for spectrum and power consumption

• Open IT platform for services and application injection

IBM Research is leading the technology of IT-based Software-defined radio in the world

• Collaboration with top operators, e.g. China Mobile, SK Telecom

• Successful demo in global industry events

Tech Park



Four key Technologies IBM is working on are key for Internet of Things

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Program Learn

Natural

Language

Analytics

DeepQA

Cognitive

Computing

“SyNAPSE”

Silicon

Devices

Nano

Scale

Workload

Optimised

Systems

Exascale

Software

Defined

Environments

1 Billion

Transistors

Data

1,000X

1 Trillion Devices

Nano

Systems

1,000,000X

1,000X

Big Data: Real-

time

Inference &

Knowable

Future



Cognitive computing aims to evolve to entirely new computing architectures and programming paradigms.

10

This poet wrote to a friend, “We are by September and yet my flowers are as bold as June. Amherst hasgone to Eden.”

Specific questions

Statistical analytics

Statistical ranking

Batch training

Rich problem scenarios

Interactive dialogue

Evidence profiles

Continuouslearning

Current Future



Cognitive computing will be central to many future applications

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Sensor Networks / Internet of Things

Infrastructure

Buildings

Vehicles

Grids

Metering

Billions of end points

100K+ elements,10ms latency

Multiple feedback time-scales

Social Business

Five-in-FiveWatson

Human and knowledge capital analytics

TM

Cognitive Sensing Technology:

• Hearing and voice recognition

• Extracting knowledge from pixels

• Sniffing for healthiness

• Haptic technology for retail

• Healthier molecular based recipes

Hearing

Smell

Taste

Sight

Touch



From research - to battling humans on Jeopardy! - to changing the way the world thinks, acts and operates

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R&D

Demonstration

Commercialization

Cross-industry Applications

IBMResearch Project (2006 – )

Jeopardy!Grand Challenge(Feb 2011)

Watson forHealthcare(Aug 2011 –)

Watson Industry Solutions(2012 – )

Watson for Financial Services(Mar 2012 – )

Expansion



Watson infrastructure comprises a platform with capabilities to address specific smarter planet areas

13

Watson for Healthcare

Watson for Client Engagement

Watson for Industry

Advisor Solutions Advisor Solutions

Uti

lizat

ion

On

colo

gy

Car

dia

c

Dia

be

tes

Cal

l Ce

nte

r

He

lp D

esk

Kn

ow

led

ge

Tech

nic

al

Model Train LearnSource

Workload Optimized Systems

Analytics MobileNLP & Machine Learning

Big Data Cloud

ASK Services DECISION ServicesDISCOVER Services

Watson For Financial Svcs.

Advisor Solutions

Ban

kin

g

Inst

itu

tio

nal

Re

tire

me

nt

Inst

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Context Value

Name Anne

Age 76

Location outdoors, Miami, FL

Symptoms dizzy, fainting

Time 3:40 PM

Context Value

Chronic Illness Diabetes

Travel 3 hrs flight today

Weather conditions 97 degrees,90% humidity

Diagnosis Dehydration

Treatment Recommended

IV rehydration therapy

Wellness Program Provider

StayWell Health Insurance

Healthcare PoA Daughter, On file

Treatment Location Recommended

Nearest Urgent Care center

Estimated Cost $300

Context Value

Medical History EMR

History of CHF yes

Last CHF episode Aug. 9, 2002

Risk of CHF recurrence without Cardiac protocols

60%

Family Support Network

Dedicated

Treatment Location Recommended

Cardiac Care

Estimated Cost $1500

CHF Cost Risk $100,000

Context Value

Cardiac protocols authorized

yes

Fast-track triage authorized

yes

Closest Cardiac Care location

201 Ridge Rd, Miami, FL

Traffic delay estimate

10 minutes

Estimate Time of Arrival

4:30 PM

CC Staff notified yes

Cost Averted $85,000

Anne, a 76 year old grandmother, becomes dizzy and faints during an outdoor event in midsummer heat and humidity

Anne’s daughter contacts her in-App PA and requests guidance. From smart device, PA sees Anne’s diabetes, recent long flight and the local weather, determines she is seriously dehydrated, recommends IV rehydration therapy and notifies Wellness program provider.

Wellness program provider engages OTTER to evaluate Anne’s entire medical history. Watson MD notices a cardiac event and congestive heart failure (CHF) 10 years prior. Recommends rehydration therapy only at a cardiac care center due to risk of triggering recurrence of CHF.

Wellness program provider authorizes fast-tracking Anne through triage directly to the cardiac care unit for rehydration therapy. Nearest cardiac care center location (given current traffic) is forwarded to Anne’s daughter’s vehicle for transport.

MD OTTER

In healthcare, for example, contextual services combine many sources of data to benefit patients and providers

© 2013 IBM Corporation15

Future

Rapidly changing workloads,

dynamic patterns

Dynamic automatic

composition of heterogeneous

system

Autonomic and proactive

management

Current

Workload virtualized, to cloud

Diverse workload, limited

patterns

Homogeneous resource

pooling

Expert configuration and

mapping of workload

Today’s environment are making workloads (and Networks) more volatile

Traditional

Few, stable, and well known

workloads

Fixed System hardware,

manual scaling

Hardwired workload, minimal

configuration

W1 W2 W3 W4

R1 R2 R3

Volatile workload characteristics result from changing business requirements

V1 V2 V3 V4 V5 … Vn

V1 V2 V3 V4 V5 V5 ... …. Vn

C

C

Source: IBM Global Technology Outlook 2013

© 2013 IBM Corporation16

.

Workload Abstraction

Functional and non-functional requirements

that may be discovered as well as specified

Resource Abstraction

Semantically rich abstractions of

heterogeneous resource capabilities and

system components

Mapping to resource

Map requirements to potential system

architectures. Proactively orchestrate

infrastructure and workload

Continuous Optimization

Autonomously construct available system

architecture to optimize workload outcome

Agility

EfficiencyConsumability

Software Defined Environments provides abstractions of workloads, services and infrastructure and an end-to-end mappings



Summary

17

CLOUD

BIG DATA

COGNITIVE SYSTEMS

SDE

INTERNET

OF

THINGS



18

Thank you

Rob van den Dam

Global Telecom Industry Leader


[email protected]

www.ibm.com/iibv