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Behind Today’s TrendsThe Technologies Driving Change

Sameer M. Prabhu, Ph. D.

Industry Marketing Director

MathWorks

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Big Data

Cloud Computing

MOOC

Industry 4.0

Internet of Things

Wearable Tech

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Smart Phones

Software as a Service

Social Computing

Executable Internet

Complex Event Processing

Trends from 2009

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Big Data

MOOC

Software as a Service

Social Computing

20142009 2010 2011 2012 2013

Google Trends over Time

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TRENDS

COME AND GO

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Research & Development

Source: OECD Main Science and Technology Indicators Database, 2014/1.

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Research & Development

R&D investment by the world’s top 2000 companies

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Long-Term Transformations Driving Changes

in Markets and Technical Applications

Spreading into every industry

Complexifying systems

Speeding up development cycles

Intensifying applied research

Challenging the education systems to produce those

skillsets

Our strategy, based on what those transformations

imply for the long term

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Algorithms in everything

People computing anywhere

Hardwarein specializedform factors

Connected chips, devices & systems

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ALGORITHMS

IN EVERYTHING

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Intel predicts

170 billiontransistors

per person

in the world by 2015

1980 1985 1990 1995 2000 2005 2010 2015

200xIN 10 YEARS

Transistors Worldwide

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TEXTUAL &

GRAPHICAL

% Compute Kalman Gain:

W = P*M'*inv(M*P*M'+ R);

% Update estimate

xhat = xhat + W*residual;

% Update Covariance Matrix

P = (eye(4)-W*M)*P*(eye(4)-W*M)' + W*R*W';

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Simulink

Stateflow MATLAB

Simulink

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MATLAB System block

Incorporate MATLAB System objects into a Simulink model

– System objects simplify the implementation of stream processing

– Optimized to process large streams of data

NEW in Release 2013b

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Signal processing

algorithm development

Basic math

Advanced digital

signal processing

Rapid iteration for

development and testing

Growing library of

algorithms

DSP System Toolbox

メディカルトラック @13:00から

http://www.mathworks.com/medical-devices/

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Phased Array System Toolbox

Algorithm

development

• Antenna array design

and analysis

• Radar signal

generation

• Detection and signal

processing algorithms

Radar system

modeling

• Performance testing

• Regulatory

compliance

• What-if analysis

NEW in Release 2014bBlock library for phased

array system design in

Simulink

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Large

Collectionof Function

Libraries

Mathematical

Modeling

Data Analysis

Computer Vision and

Image Processing

Computational

Finance

Control Systems

Communications

Digital Signal

Processing

Physical Modeling

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Advanced Driver Assistance Systems

From Advance Driver Assistance Systems Market,

Drivers, Functions , Continental AG, KSAE 2011

Adaptive cruise

control + Stop&Go

Forward collision

warning

Emergency brake

assist

Advanced

emergency braking

system

Traffic signal

recognition

Intelligent headlamp

control

Lane change assist

Back-up aid

Lane departure

warning

Lane keeping

system

Blind spot detection

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Design, Analyze, and Implement Radar Sensors' Alignment Algorithm with MATLAB

Ling Ma, Delphi, MathWorks Automotive Conference, May 2014, Michigan, USA.

Advanced Driver Assistance Systems

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Traffic sign recognition in driver assistance systems - MATLAB at Continental

Dr Alexander Behrens, Continental, MATLAB Expo, July 2014, Munich, Germany.

Advanced Driver Assistance Systems

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APPS

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Control System Tuner App

Tune fixed-structure

controllers in Simulink

Specify blocks to tune

Add tuning goals

Visualize tuning results

Update tuned Simulink

blocks from app

NEW in Release 2014a

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User-Created Apps

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Unified textual & graphical programming

Portfolio of libraries

Apps and resources on MATLAB Central

ALGORITHMS

IN EVERYTHING

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HARDWARE

IN SPECIALIZED

FORM FACTORS

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RUN YOUR ALGORITHM

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Power plants 100sCars

1,000,000s

Planes

1,000s

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HIL Simulator

Real-Time Test System USB Plug-In Device

Microcontroller

Programmable SOC

Custom ASIC

MicroprocessorXilinx Zynq Intelligent Drives Kit

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Simulink Real-Time Explorer

Build, run, and test real-time applicationsSimulink Real-TimeNEW in Release 2014a

"Simulinkのバーチャル環境を現実の世界へ" @ 17:30

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Run algorithms on

real-time hardware

– Real-time testing

and verification

Design iteration and

testing in minutes

Higher software

quality

Simulink Real-TimeRelease 2014a

“…with Model-Based Design and rapid real-time prototyping, we maintain the product development

pace that our business demands.”

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The Rise of Low-Cost

Hardware for the Masses

Arduino

300,000+ commercially produced

$30 (UNO), $55 (Mega 2560), $55 (Due)

Raspberry Pi

2.5+ million shipped

$35 (Model B)

LEGO Mindstorms EV3

3rd generation from

LEGO Mindstorms

$350 (for base set)

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NEW in Release 2014b

Hardware

support

packages

• Get connected

and running

quickly

• 150 packages

today,

for ARM, Texas

Instruments,

iPhone, Android,

Kinect, and more

MathWorks.com/hardware

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Magnus Egerstedt

Khepera 3

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HARDWARE

IN SPECIALIZED

FORM FACTORS MATLAB algorithms in production systems

Code generation for prototyping and embedded

Connecting to low-cost hardware for the masses

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CONNECTED

CHIPS, DEVICES,

& SYSTEMS

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Internet of Things

1875 1900 1925 1950 1975 2000 2025

“Place” connectivity

PEOPLE 5 billion“People” connectivity via

mobile devices

THINGS 50+ billion

“Thing” connectivity

INFLECTION

POINTS

Growth in Global Connectivity

PLACES 1 billion

© 2010 Ericsson AB – from Joshipura, Arpit, “Infrastructure Innovation - Can

the Challenge be met?” Global Semiconductor Alliance, September 2010

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Megabyte 1,000,000 bytes (million)

Gigabyte 1,000,000,000 bytes (billion)

Terabyte 1,000,000,000,000 bytes (trillion)

Petabyte 1,000,000,000,000,000 bytes (million billion)

Exabyte 1,000,000,000,000,000,000 bytes (billion billion)

Source: General Electric

Turbine

(machine)

Wind farm

(plant)

Energy Producer

(enterprise)

Analytics Asset optimization

Operations

optimization

Business optimization

Data

quantity >100 tags >6,000 tags >1M+ tags

Data

frequency 40 milliseconds 1 second 1 second – 10 minutes

17 MB/day

6.3 GB/year

4.1 GB/day

1.5 TB/year

0.7 TB/day

0.25 PB/year

Big Data in Energy Production

"インテージ株式会社: 価格弾力性分析におけるMATLAB活用事例の紹介" @17:10

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Big Data in Many Industries

Exabyte 1,000,000,000,000,000,000 bytes (billion billion) ENERGYSmart grid

FINANCEFraud detection

AUTOFleet data will

influence vehicle design

AEROMaintenance, reliability

BIOTECHInstrumented humans

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Big Data in MATLAB

Memory &

Disk Management

64-bit

Memory Mapped Variables

Disk Variables

Intrinsic Multicore Math

Image Block Processing

Processing Speed

GPU Computing

Parallel Computing

Cloud Computing

Distributed Arrays

Algorithms

Streaming Algorithms

Machine Learning

PROCESSING OPTIONS

• MATLAB RESTful interface to Cluster

• MATLAB Hadoop Streaming

• NoSQL connector (e.g. mongo)

• MATLAB / Java App accessing Cluster

• MATLAB Map-Reduce Components

"エンタープライズ向けアプリケーション開発の例"@15:50

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CONNECTED

CHIPS, DEVICES,

& SYSTEMS Memory management

Computing power

Advanced algorithms

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PEOPLE

COMPUTING

ANYWHERE

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Cloud as a New Platform

1,000s of applicationsMILLIONS of users

Terminal - mainframe, mini

HUNDREDS OF MILLIONS

of users10,000s of applications

PC - LAN, Internet

BILLIONS of users

Cloud – mobile, browser, social, big data

MILLIONS of apps

Source: IDC, 2013

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MATLAB MobileSupport for iPhone, iPad & Android

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The cloud, enhancing your

MATLAB DesktopMATLAB Distributed Computing Server on Amazon EC2

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The cloud, running

MATLAB, on demand, from anywhere

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The cloud, running

MATLAB, on demand, from anywhere

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MATLAB Production Server

Deploy MATLAB analytics into

enterprise IT frameworks

Integrate with databases,

webservers

and application servers

Seamless transition from algorithm

prototyping to enterprise-scale

analytics without recoding

“This product is a game changer, for sure.”

—

Quantlabs

Running in Enterprise IT Environments

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PEOPLE

COMPUTING

ANYWHERE MATLAB on mobile devices

MATLAB on the cloud

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Algorithms in everything

People computing anywhere

Hardwarein specializedform factors

Connected chips, devices & systems

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MOOCs

MOOC = Massive Online Open Course

Online course

Unlimited participation

Open access via the web

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Magnus Egerstedt

Khepera 3

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Algorithms in everything

People computing anywhere

Hardwarein specializedform factors

Connected chips, devices & systems