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Making sensor information and big data useful for customers

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Making sensor information and big data useful for customers Nottingham September 24th Dr. ing. Bendert de Graaf, Manager Operations Office Laboratory
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Page 1: Making sensor information and big data useful for customers

Making sensorinformation and big datauseful for customersNottingham – September 24th

Dr. ing. Bendert de Graaf,Manager Operations Office Laboratory

Page 2: Making sensor information and big data useful for customers

IntroductionVitens in numbers:• Customers: 5,4 million• Connections: 2,4 million• Production locations: 97• Production: 330.000.000 m3• Distribution network: 48.000 km• Employees: 1400

Page 3: Making sensor information and big data useful for customers

Drinking water | Laboratory

Laboratory• Automated• 350.000 samples per year• 675.000 analyses per year

Page 4: Making sensor information and big data useful for customers

Black box?

• Water quality: too late• Leakage: reactive• Energy: suboptimal• Customer comm.: reactive

• Water quality: real-time• Leakage: real-time• Energy: optimal• Customer comm.: Proactief

The need for

intelligent water supply

Page 5: Making sensor information and big data useful for customers

Vitens Innovation Playground

Page 6: Making sensor information and big data useful for customers

4 programsCu

stom

erin

tera

ctio

nLe

ak d

etec

tion

and

loca

lizat

ion Real-tim

e WQ

Energyreduction

ICTData

Page 7: Making sensor information and big data useful for customers

Real-Time Water Quality

Real-time W

Q

ICTData

Cust

omer

inte

ract

ion

Energyreduction

Leak

det

ectio

nan

d lo

caliz

atio

n

Page 8: Making sensor information and big data useful for customers
Page 9: Making sensor information and big data useful for customers

Leak detection and localization

Real-time W

QEnergyreduction

ICTData

Leak

det

ectio

nan

d lo

caliz

atio

nCu

stom

erin

tera

ctio

n

Page 10: Making sensor information and big data useful for customers

CWV dashboardPhonecalls

Page 11: Making sensor information and big data useful for customers

Easter Monday 10:45 AM

Page 12: Making sensor information and big data useful for customers

Time Lapse - Leak

All incoming calls

AnsweredBounced

Page 13: Making sensor information and big data useful for customers

Real-time social media

Page 14: Making sensor information and big data useful for customers

Special and Vulnerable customers

Page 15: Making sensor information and big data useful for customers

Real-time dashboard

Water distribution control roomCustomer service

Service Engineers

Phone call

Tweet

WQ sensor

DBM leakage monitor

Page 16: Making sensor information and big data useful for customers

Serious Gaming

Page 17: Making sensor information and big data useful for customers

Customer focussed processEvents like pipe burst or WQ issue

Immediate data dumpof customer mail/cellphone numbers in thisspecific area code

Inform customer by mail,sms and social mediaabout the event beforehe is trying to contact thecall centre

90% reductioncapacity call centreand increase ofcustomer satisfaction

Page 18: Making sensor information and big data useful for customers

In conclusion

Page 19: Making sensor information and big data useful for customers

More Informationhttp://sw4eu.com/

Page 20: Making sensor information and big data useful for customers
Page 21: Making sensor information and big data useful for customers

Vitens Innovation Playground

• 100.000 households• 2270 km network (5%)• 750 km2• 6 DMA’s• 106 Sensors added:

• 23 Flow• 23 Pressure• 15 Conductivity• 45 Eventlab

Page 22: Making sensor information and big data useful for customers
Page 23: Making sensor information and big data useful for customers
Page 24: Making sensor information and big data useful for customers

Vitens Strategy 2015-2017Two Strategic company goals:

1. Customer Excellence2. Sustainable use of sources and assets

Nine strategic programs:Customer Excellence1. Proactive customer communication2. Genuine customer focus3. Our company DNA (craftsmanship , groundbreaking, customer focus)4. Increase attractiveness VitensSustainable use of sources and assets5. Continuity in process automation6. Effective asset management7. Future infrastructure: from labour to data driven8. Increase water authority position9. Control our natural sources

Page 25: Making sensor information and big data useful for customers

Energy Reduction

Energyreduction

ICTData

Cust

omer

inte

ract

ion

Leak

det

ectio

nan

d lo

caliz

atio

n Real-time W

Q

Page 26: Making sensor information and big data useful for customers

Pressure management

Current situation (nul):- Pressure measurement

directly after pump

Experimental setup:- Pressure measurement

at customer

Page 27: Making sensor information and big data useful for customers

Dynamic pressure management

Druk sturing Serie 1 Serie 2 Serie 3 Gemiddeld Percentage

energie

Munnekeburen kWh/m3 kWh/m3 kWh/m3 kWh/m3 verlaging

0-meting 0,324 0,320 0,321 0,322

Proef 0,298 0,294 0,294 0,295 8,3 %

1% = ~ €170.000

Page 28: Making sensor information and big data useful for customers

Explanation:

18:4420:3320:1718:49

1:20

16 November

20:2122:41

12:30

15:08Power Outage‘Colored water’:problems starting updecoloration

‘Uncolored water’:decoloration started‘Uncolored water’:decoloration started‘Colored water’:problems starting updecoloration

‘Uncolored water’:decoloration started‘Colored water’ hasarrived‘Colored water’ hasarrived‘Uncolored water’ hasarrived15:44‘Uncolored water’ hasarrived2:05‘Uncolored water’ hasarrived

6:37

3:00

‘Uncolored water’ hasarrived‘Uncolored water’ hasarrived

17 November18 November

Page 29: Making sensor information and big data useful for customers

Hours faster1. Gorredijk: 4,5 hours faster2. Oosterwolde-Drachten: 2 hours faster3. Drachten: 3 hours faster4. Oosterwolde-Drachten: 8 hours faster5. Gorredijk: 4 hours faster

11 22 33

5544

Page 30: Making sensor information and big data useful for customers

MicrobiologyTraditional culturing method (1-5 days)

• Total plate count• E. coli• Enterococcus• Aeromonas• Legionella

Confirmation with PCR/MaldiTOF (few hours)

Page 31: Making sensor information and big data useful for customers

Drinking water | Strategy

Strategy

Page 32: Making sensor information and big data useful for customers

Number of tests performed at theLaboratory

• Inorganic : 77 tests• Organic : > 500 target components

: LC and GC screening methods• Microbiology : 17 tests (microbiology, confirmed

with QPCR and MALDI-TOF)

Page 33: Making sensor information and big data useful for customers

What’s next with WQ in SW4EU?

• Install ~40 more Eventlab sensors• Install ~10-15 S::Can I::Scan sensors• Install ~10-15 Intellitect sensors• Test, validate and use in the VIP the Bactiline sensor• Change the WQ in the VIP• Perform PCA analyses


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