Hive
Big Data Meetup
2
Agenda – 3 Key Things
1. Deep dive & Explore Smart meter M2M Use Case
2. How M2M unlocks value in Oil N Gas, Building ri...
3
What's common to Cows in Netherland & New Zealand ?
4
`2008 : Sensors > Humans !Unnoticed inflection point ... Nose to tail sensor jungle
Sensors Humans
5
How M2M + Big Data Analytics is disrupting the Energy industry ?
6
The Electricity Value chain
Power generation Transmission substation
High voltage electric transmission system
Distribut...
7
Upto 40 % of Power transmitted does not reach end consumer
Distribution considered the weak link
Why is Distribution con...
8
Pain-1 : Large Scale Theft !
9
Which grid components need to be
replaced based on age and outage
frequencies ?
Pain-2 : Ageing + inadequate distributio...
10
How do we map street level outage360 behaviour ?
proactive incident response
Pain-3 : Frequent Outages
11
Pain-4 : Grid energy spot pricing ...
Load forecasting !
12
Pain-5: Sub Optimal
use of electricity by
households
Inefficient bulbs
Switching from inefficient incandescent
lights t...
13
• Where should Electricians to be
deployed to the right spots in
real time
• Where should they be deployed
to proactive...
14
Why is it important to solve this problem?
A 1 % reduction in AT&C unlocks millions of $
15
How does a Smartmeter help ?
• Smart meter Data collected
• COV
– Voltage
– Current
– Power
– Harmonic voltage distorti...
16
So what are the Smartmeter use cases driving
ROI for utility industry ?
17
Tamper Loss Spotter - Bird’s  Eye  View
18
Tamper loss spotter- Worms Eye View
19
Dynamic electric pricing
•Time of use rates
•Encourage consumers
to use less power a peak
rates
•Reducing the need for
...
20
Analyzing frequent Smartmeter
sequences
X
1
2
3
4
Day-1 9:12 am
Fuse blowout
Day-6 3:15 pm
Line
Maintenance
Inspection
...
21
Chillers + Boilers Heavily
instrumented
Flow sensors
Steam pressure
sensors
Temperature
sensors
Status sensors
22
Command centres : Real time streaming sensor data
23
M2M Big Data Solution architecture
1
2
3
4
Command centre
Field Technicians
Head office Design
Process Optimizers
Reduc...
24
What are the 3  important  “Gotchas”  for  M2M  +  
Big Data Analytics from the trenches ?
25
Gotcha-1: TRIANGULATE SIGNALS ACROSS DEVICES/MANUFACTURERS !
Cast  a  wide  net  in  “sensor  data  ocean”  to  triangu...
26
Gotcha-2 : Machine learning @ scale
Harvest signals and patterns from streaming sensor data- 3 techniques
• Sequence
• ...
27
Gotcha-3 : Gamification + Habit Design
Applied Behavior Psychology in Design
Gamification + Habit Design
Deep Machine L...
28
When you
flush
sensor
event data
lives are at
risk !!!
Sensor event streams
being flushed
Lives being saved
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Flutura presentation - The Hive india event

  1. 1. Hive Big Data Meetup
  2. 2. 2 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
  3. 3. 3 What's common to Cows in Netherland & New Zealand ?
  4. 4. 4 `2008 : Sensors > Humans !Unnoticed inflection point ... Nose to tail sensor jungle Sensors Humans
  5. 5. 5 How M2M + Big Data Analytics is disrupting the Energy industry ?
  6. 6. 6 The Electricity Value chain Power generation Transmission substation High voltage electric transmission system Distribution Substation Voltage is reducedDistribution Transformer Household Generation + Transmission + Distribution
  7. 7. 7 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 ?
  8. 8. 8 Pain-1 : Large Scale Theft !
  9. 9. 9 Which grid components need to be replaced based on age and outage frequencies ? Pain-2 : Ageing + inadequate distribution network
  10. 10. 10 How do we map street level outage360 behaviour ? proactive incident response Pain-3 : Frequent Outages
  11. 11. 11 Pain-4 : Grid energy spot pricing ... Load forecasting !
  12. 12. 12 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!
  13. 13. 13 • 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!
  14. 14. 14 Why is it important to solve this problem? A 1 % reduction in AT&C unlocks millions of $
  15. 15. 15 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  
  16. 16. 16 So what are the Smartmeter use cases driving ROI for utility industry ?
  17. 17. 17 Tamper Loss Spotter - Bird’s  Eye  View
  18. 18. 18 Tamper loss spotter- Worms Eye View
  19. 19. 19 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.
  20. 20. 20 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 ?
  21. 21. 21 Chillers + Boilers Heavily instrumented Flow sensors Steam pressure sensors Temperature sensors Status sensors
  22. 22. 22 Command centres : Real time streaming sensor data
  23. 23. 23 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
  24. 24. 24 What are the 3  important  “Gotchas”  for  M2M  +   Big Data Analytics from the trenches ?
  25. 25. 25 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
  26. 26. 26 Gotcha-2 : Machine learning @ scale Harvest signals and patterns from streaming sensor data- 3 techniques • Sequence • Frequent sequences • Large graph • Text mining
  27. 27. 27 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
  28. 28. 28 When you flush sensor event data lives are at risk !!! Sensor event streams being flushed Lives being saved

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