Data Intensive Engineering

Xosé Manuel Carreira Rodríguezhttp://www.linkedin.com/in/carreira

13th December 2012

BRIEF

• In this presentation the possible use of the big

data technologies in the civil engineering is

overviewed.

“…probably indicates that these sectors face

strong systemic barriers to increasing

productivity”

We collect enough data.

We need to focus on

1- connecting

2 – identifying patterns

3- giving confidence level

Multiple data sources:

BooksExperts in the fieldInformation systemsTests and surveyingData repositoriesReal time sensors

Data quality

• Processing is cheap and access is easy, the big problem is data quality.

• Considerable research but highly fragmented

Classic definition of Data Quality

• Accuracy

– The data was recorded correctly.

• Completeness

– All relevant data was recorded.

• Uniqueness

– Entities are recorded once.

• Timeliness

– The data is kept up to date.

• Special problems in federated data: time consistency.

• Consistency

– The data agrees with itself.

Finding a modern definition

• Data quality must

– Reflect the use of the data

– Lead to improvements in processes

– Be measurable

• No silver bullets: Use several data quality

metrics.

What is the problem to solve?

• Do you have a bunch of data and want to:– Estimate an unknown parameter from it?

• True rainfall based on radar observations?

• Amount of liquid content from in-situ measurements of temperature, pressure, etc?

• Regression

– Classify what the data correspond to?

• A water surge?

• A temperature inversion?

• A boundary?

• Classification

• Regression and classification aren’t that different

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Case 1: Neural networks for flood

• Neural networks modelling of the rainfall-runoff relationship

• No physical model, just data driven model.

• Result: flow forecasting

Case 1: Neural networks for flood

• Input: several past rain gauges and flow gauges

• Result: Flow model

Case 1: Neural networks for flood

Training with 1st (larger) set of data

Case 1: Neural networks for flood

Verification with 2nd (smaller) set of data

Simulation

sample

How can IT help in maintenance ?

• Information Technology has also found applications in post commission period of the project.

• IT can provide easy access to various statistics, drawing & various other data concerning the project.

• Self check tools can identify the problems in various systems like fire fighting, air conditioning & can automatically inform concerned service provider.

• IT can also help in prompt reporting of problem & its rectification.

Case 2: Bridge Management Systems

• Double click on the

icon on your desktop

– Introductory screen is

displayed

– Click OK button to

continue to the Data

collection form

Page 18

Connecting Bridge Management Systemsto Asset Management

U.S. Department of Transportation

Federal Highway Administration

Bridges in the U.S.

25% are structurally or functionally deficient according to ASCE

0

20000

40000

60000

80000

100000

120000

140000

Pre

-1909

10s

20s

30s

40s

50s

60s

70s

80s

90s

Bridge Construction by Decade

Typical BMS Expectations

A tool to evaluate:

• Bridge condition and serviceability

• Implications of project decisions

• Priorities and schedules

• Expected budget

• Cost of alternative standards

• Value of preventive maintenance

Case 2: Bridge Management Systems

You can run a company from a coffee shop

Why not a lab or a civil infraestructure?

Desktop PCs are idle half the day

24

Desktop PCs tend to be active

during the workday.

But at night, during most of

the year, they’re idle. So

we’re only getting half their

value (or less).

Finally ,

it is argued that IT can readily be

used by civil engineers given the low

capital investment levels required.

The “only” requirement is investment in

education among the civil engineers &

recognition of the enormous potential

lying beneath.