From Big Engineering Data to Insights using MATLAB Analytics file2 Gathering Insight from Big...
Transcript of From Big Engineering Data to Insights using MATLAB Analytics file2 Gathering Insight from Big...
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1© 2014 The MathWorks, Inc.
From Big Engineering Data to Insights using
MATLAB Analytics
Arvind Hosagrahara
Principal Technical Consultant
[email protected] (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.