flutura presentation - the hive india event

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Hive Big Data Meetup

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Page 1: Flutura presentation - The Hive india event

Hive

Big Data Meetup

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Agenda – 3 Key Things

1. Deep dive & Explore Smart meter M2M Use Case

2. How M2M unlocks value in Oil N Gas, Building risk & Telecom ?

3. 3  key  “gotchas”  from  the  trenches

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What's common to Cows in Netherland & New Zealand ?

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` 2008 : Sensors > Humans ! Unnoticed inflection point ... Nose to tail sensor jungle

Sensors Humans

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How M2M + Big Data Analytics is disrupting the Energy industry ?

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The Electricity Value chain

Power generation Transmission substation High voltage electric transmission systems

Distribution Substation Voltage is reduced

Distribution Transformer

Household

Generation + Transmission + Distribution

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Upto 40 % of Power transmitted does not reach end consumer

Distribution considered the weak link

Why is Distribution considered a weak link in the entire power value chain ?

What's the Problem we are solving ?

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Pain-1 : Large Scale Theft !

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Which grid components need to be replaced based on age and outage frequencies ?

Pain-2 : Ageing + inadequate distribution network

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10 How do we map street level outage360 behaviour ?

proactive incident response

Pain-3 : Frequent Outages

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Pain-4 : Grid energy spot pricing ... Load forecasting !

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Pain-5: Sub Optimal use of electricity by

households

Inefficient bulbs

Switching from inefficient incandescent lights to more efficient light bulbs such

as compact fluorescent lights (CFLs)

ALTERING HOUSEHOLD BEHAVIOR KEY!

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• Where should Electricians to be deployed to the right spots in real time

• Where should they be deployed to proactively prevent outages

Pain-6: Optimising Field Electrician force!

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Why is it important to solve this problem?

A 1 % reduction in AT&C unlocks millions of $

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How does a Smartmeter help ? • Smart meter Data collected

• COV

– Voltage – Current – Power – Harmonic voltage distortion

• Events

– Tamper events • Reverse energy flows

– Outage events – Meter hardware events

• Battery low events • Signal strength low

– Device status events • “Last  gasp”, • “Power  restore”  events  

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So what are the Smartmeter use cases driving ROI for utility industry ?

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Tamper Loss Spotter - Bird’s  Eye  View

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Tamper loss spotter- Worms Eye View

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Dynamic electric pricing

•Time of use rates •Encourage consumers to use less power a peak rates •Reducing the need for expensive generating stations that only operate for brief periods.

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Analyzing frequent Smartmeter sequences

X

1

2

3

4

Day-1 9:12 am Fuse blowout

Day-6 3:15 pm Line Maintenance Inspection

Day-9 10:15 pm Transformer or Eco system device recalibration

Day-11 3:15 pm Three 2 sigma Voltage Surge Event occurred Within 24 hours

Day-12 3:15 pm Power Outage Breaks down

X

X

X

X

X

X

X

X

X

X

X

1. Is it Electrician ?

2. Is it Calibration ?

3. Is it Load ?

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Chillers + Boilers Heavily instrumented

Flow sensors

Steam pressure sensors

Temperature sensors

Status sensors

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Command centres : Real time streaming sensor data

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M2M Big Data Solution architecture

1

2

3

4

Command centre

Field Technicians

Head office Design

Process Optimizers

Reduce Massive Risks + Unlock Process efficiency

Digital Oil Field

Smart Buildings

Smart Meter grid

Telecom

R E A L

T I

M E I N G E S T I O N

Deep Machine Learning

Complex Machine

Vectorisation Gamification

and Habit design

Triangulated Markers

Massively Scalable

Sensor Data Ocean

Real time sensor event pipelines

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What are the 3  important  “Gotchas”  for  M2M  +  Big Data Analytics from the trenches ?

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Gotcha-1: TRIANGULATE SIGNALS ACROSS DEVICES/MANUFACTURERS ! Cast  a  wide  net  in  “sensor  data  ocean”  to  triangulate  on  multi  device  signals across multiple real time event streams

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Gotcha-2 : Machine learning @ scale Harvest signals and patterns from streaming sensor data- 3 techniques

• Sequence

• Frequent sequences

• Large graph

• Text mining

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Gotcha-3 : Gamification + Habit Design Applied Behavior Psychology in Design

Gamification + Habit Design Deep Machine Learning

Hadoop Cluster + NoSQL Persistence

Real time streaming data pipelines

80 % Of work

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When you flush

sensor event data lives are at

risk !!!

Sensor event streams being flushed

Lives being saved