1© 2014 The MathWorks, Inc.

From Big Engineering Data to Insights using

MATLAB Analytics

Arvind Hosagrahara

Principal Technical Consultant

Arvind.Hosagrahara@mathworks.com (248-596-7939)

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Gathering Insight from Big Engineering Data

Problem statement:

“Democratization of Data (analytics)” –

making analytics available to ALL users in an

organization, from the data scientists to

product engineers and business analysts. [1]

[1] http://www.forbes.com/sites/davefeinleib/2012/07/16/6-insights-from-facebooks-former-head-of-big-data/

[2] http://papers.sae.org/2010-01-1997/

Data, data, everywhere.

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Demo: A Simple Enterprise Application Example

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Fleet Analysis Setup

OBD2 Data from a variety of

automobiles.

COTS hardware ($8-10)

Off-the-shelf logging software

Torque-BHP (Android)

Samsung Galaxy Note® II

AT&TTM 4G, AmazonTM EC2TM,

ApacheTM Hadoop®

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Behind the Scenes: The Extract-Transform-Load pipeline

OBD2 Bluetooth 4G LTE

HTTP

LAMR Stack

Hadoop Ecosystem

Deployed

MATLAB

MATLAB

Desktop

Apache, the Apache feather logo, Hadoop are registered trademarks or trademarks of the Apache Software Foundation

AmazonTM EC2TM

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Behind the Scenes: Analysis to Production

From Prototype to Production

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Insights (Engine Fuel Consumption and Efficiency)

Understanding of Real-world

driving patterns

Design Value based on calibration

driven by real world data

Optimization of Fuel Consumption

and Shift Schedules

Driver Variability (FFT of Throttle

Position)

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Insights (Engine Fuel Consumption and Efficiency)

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Insights (8 mile traffic)

Traffic Patterns (the case for roundabouts)

0.0351 Gal/car at the intersection

12 cars a minute on the average

A saving of 121.3 gallons of

gasoline per day if the traffic lights

were replaced with a round-about.

A rough saving of 4.5 million

pounds of CO2 per year.

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Typical Pains

CAN Data Analysis

– CAN data available as multiple files

that are “too large”

Data Logger : Vector GL1000/2000

One 32-Gbyte SD Card /1 test car, 1

month

Typical annual data intake

– 4-14 Tb (industrial automation OEM)

– 7-20 Tb (automotive OEM)

Historical and Archive Data

– Petabyte scale data from old

programs and fleet programs

Many kind of Signals

– About 100 (Speed, Fuel, Temperature,

GPS, etc…)

– Sampling Rate:

10msec,100msec,1000msec

Many analysis items: over 200 Values on specific event

Min, Max, Average, Sum

Graph, Histogram Chart, Scatter Chart

Need for advanced analysis and

visualization

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Automotive specific engineering pains and use-cases

Proprietary File Formats

– MDF

– BLF

– CLF

Use Cases

– Dyno Data

– DriveCycle / EPA

– Fleet Data (BlackBox)

– Proving Ground Test data

Integration with Standard Data

Storage Systems

– ASAM ODS

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MATLAB for Analysis and Visualization

Development of analysis software

for engineering applications

Leverage of existing MATLAB and

Simulink

Extensive set of toolboxes and

blocksets to make advanced

analysis possible and easy.

– Vehicle Network Toolbox

– Statistics, Optimization Toolboxes

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Enterprise Resources

Update

Workflow of Analytical Development

Analytics

Development

Create prototype

Validate ideas

Generate results

Data

Exploration

Gain insights

Build intuition

Hypothesize

Analytics

Integration

Formalize

Test & Strengthen

Deploy & share

MATLABProductionServer(s)

WebServer(s)

Excel add-ins

Desktop

Web & Enterprise

Excel EXE Web Database

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Conclusions and Questions

Techniques and Tools are available to deploy MATLAB analytics to

business / mission critical applications that work with Big Engineering

datasets.

MATLAB provides a unified powerful platform for the rapid development,

refinement and deployment of data analytics across a wide range of

automotive use cases.

MathWorks has the experience and support to help you succeed in your

project.