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©Fluturasolutions2015
6 Families of IOT Use Cases
What are real world examples of IOT Big Data Use Cases impacting
Biz Outcomes ? Flutura keenly read the market signals from Houston,
Tokyo + European markets and more specifically in the energy +
engineering industries we are focussed on . After analyzing the data
accrued over the last 24 months we have distilled it down to 6
practical IOT big data use case families .
We have heard a lot of marketing hype around IOT and Big data.At the
end of the day it boils down to
ONE POWERFUL UNANSWERED QUESTION
What are some of the measurable outcomes impacted by IOT use
cases ?
So here they come ...
2
©Fluturasolutions2015
This is the holy grail of IOT and Big data. While most IOT big data use
cases focus on cost optimisation, there are a couple of interesting use
cases which we encountered which activated new revenue streams by
tweaking the business model in the market place.
For example in the Oil and Gas industry Flutura encountered
organisations creating new revenue streams by monitoring real time
situational awareness of digitised wells as a paid value added service.
Flutura helped a provider of Smart city solutions to monitor 11000
government owned buildings in real time by watching their boiler, chiller,
fire alarm and other ambient data in real time where the pricing model
was per device.
In the deregulated REP markets, Flutura has encountered REPs offering
newvalue added offerings like energy audits and asset refinancing for
commercial industrial customers which are powered by smart meter
based big data products
6 Families of IOT Use Cases
3
©Fluturasolutions2015
Energy consumption is a
very important lever which
drives profitability in the
industrial setup. Surgically
targeting this business
outcome can really make
the business case for IOT
based big data solutions
as we now have the ability
to mine granular state
information and correlate
it to energy outcomes
Another project we executed which
was in the utility industry involved
reducing average peak
power consumed by residential
customers by analysing smart
meter data across millions of
households gathered at 15 minute
intervals
This pattern seems to be repetitive
in multiple industry context
where a single digit change in
energy/fuel efficiency has a 6
figure impact on savings
For example we recently
executed an engagement in
Houston based fleet
provider where we reduced
average fuel consumption by 2
% unlocking 65 million dollars in
savings per year. We did this by
digging deep into signals buried
in operating sensor event
streams and location related
data which was then correlated
to the fuel consumption data.
4
©Fluturasolutions2015
We worked with a leading
Spanish wind power generation
company recently who gave us
data regarding the performance
characteristics of 2 turbines
like main shaft rpm, grid
voltage, slide ring temperature,
reactive power, and rotor
characteristics at second level.
We unleashed Machine learning
algorithms on terabytes of time
series data a Hadoop cluster
and successfully extracted
signals emitted prior to a
turbine breakdown
A US Engineering giant gave us
data from Electrical trip unit
data (48 Samples/Cycle and 4
Cycles prior and post events
along with power data –
voltage, current , frequency )
which was then analysed to
spot significant differences in
trip unit calibration which
compromised asset integrity
“Smelling” asset signals is
again a recurring pattern
encountered across industries
Industrial industries are
asset intensive. For every
minute an asset is down
millions of dollars are
lost. Reducing down time
of certain nodal assets is
a use case which has a
business case. Let’s take
2 examples we executed
in this area to illustrate
this theme
5
©Fluturasolutions2015
In process and discrete
manufacturing industries, it’s
very important to keep
defects below a certain
threshold. A new set of
possibilities is being enabled
from granular data collected
from digital factories. It is
the ability to dig deep into
second level sensor data to
understand specifics of
process states which
increased defect density.
Let’s quickly take an example
of a project we executed for
a US based electrical product
manufacturer.
The product underwent a
variety of operations and at
each step of the operations
sensors were monitoring
viscosity, humidity,
temperature data at second
level and streaming it to
SCADA based Historians. We
were able to spot patterns
using advanced machine
learning techniques on
a Spark based
architecture which resulted
in a 8 % reduction in defect
density for the product
6
©Fluturasolutions2015
As the grid gets increasingly intertwined into all
the assets, security becomes a very important
consideration. Security forensics using granular
event data can help investigators analyse
sequence patterns exhibited prior to an adverse
event happening. These digital signatures can
be codified into a knowledge bank and watched
in real time. From Flutura’s experience this is
still in concept stage and pilots are being
executed to solidify the analytical workflows
which help a IOT security outcome. We will be
happy to share some solid security use cases
in the next 6 months
7
©Fluturasolutions2015
Pricing innovations using analytics is another area where we are
seeing some powerful use cases blossom.
For example, in the energy value chain trading happens in Energy
exchanges and there is a lot of data generated from trades,
competitive pricing information which needs to be mined to
understand volatility patterns and to help time the market. Flutura’s
energy data scientist are helping a major energy trade see those
invisible pricing patterns to optimise millions of dollars by timing
the market well by analysing past correlations
Another use case which is finding momentum is dynamic asset
pricing. Assets which are leased to customers (for example golf
carts are equipped with sensors which record location, topple
events, average cart speed, start, stop events). By analysing the
granular usage statistics , asset leasing companies are able to
have dynamic pricing of assets 8
©Fluturasolutions2015
We do agree that the marketing machines have been on steroids
advocating IOT and Big Data as the panacea for everything. Industrial
mindsets focus on tangible outcomes and some of the frequent
questions we hear are Are they just fads or is it real ? Where is
the business case for IOT big data in Engineering industries ? What
are the use cases which are real for the Oil n Gas industry ? How can
Retail energy providers and energy trading firms benefit from IOT and
big data ? While a lot has been done on buzz word introduction, we
felt the best way to make the case was to highlight tangible
business outcomes which are tangible and "show them the money"
As a startup we have been blessed as customers trusted us to
unlock possibilities in their machine data and convert them into
dollars. We hope you found the use case taxonomy useful and would
love to hear your experiences from the trenches.
As we say in Flutura
May the big data renaissance awake every industrial
organisation
9
©Fluturasolutions2015
www.flutura.com linkedin.com/company/flutura
Blog.fluturasolutions.com @fluturads 10
©Fluturasolutions2015

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6 use cases

  • 2. 6 Families of IOT Use Cases What are real world examples of IOT Big Data Use Cases impacting Biz Outcomes ? Flutura keenly read the market signals from Houston, Tokyo + European markets and more specifically in the energy + engineering industries we are focussed on . After analyzing the data accrued over the last 24 months we have distilled it down to 6 practical IOT big data use case families . We have heard a lot of marketing hype around IOT and Big data.At the end of the day it boils down to ONE POWERFUL UNANSWERED QUESTION What are some of the measurable outcomes impacted by IOT use cases ? So here they come ... 2 ©Fluturasolutions2015
  • 3. This is the holy grail of IOT and Big data. While most IOT big data use cases focus on cost optimisation, there are a couple of interesting use cases which we encountered which activated new revenue streams by tweaking the business model in the market place. For example in the Oil and Gas industry Flutura encountered organisations creating new revenue streams by monitoring real time situational awareness of digitised wells as a paid value added service. Flutura helped a provider of Smart city solutions to monitor 11000 government owned buildings in real time by watching their boiler, chiller, fire alarm and other ambient data in real time where the pricing model was per device. In the deregulated REP markets, Flutura has encountered REPs offering newvalue added offerings like energy audits and asset refinancing for commercial industrial customers which are powered by smart meter based big data products 6 Families of IOT Use Cases 3 ©Fluturasolutions2015
  • 4. Energy consumption is a very important lever which drives profitability in the industrial setup. Surgically targeting this business outcome can really make the business case for IOT based big data solutions as we now have the ability to mine granular state information and correlate it to energy outcomes Another project we executed which was in the utility industry involved reducing average peak power consumed by residential customers by analysing smart meter data across millions of households gathered at 15 minute intervals This pattern seems to be repetitive in multiple industry context where a single digit change in energy/fuel efficiency has a 6 figure impact on savings For example we recently executed an engagement in Houston based fleet provider where we reduced average fuel consumption by 2 % unlocking 65 million dollars in savings per year. We did this by digging deep into signals buried in operating sensor event streams and location related data which was then correlated to the fuel consumption data. 4 ©Fluturasolutions2015
  • 5. We worked with a leading Spanish wind power generation company recently who gave us data regarding the performance characteristics of 2 turbines like main shaft rpm, grid voltage, slide ring temperature, reactive power, and rotor characteristics at second level. We unleashed Machine learning algorithms on terabytes of time series data a Hadoop cluster and successfully extracted signals emitted prior to a turbine breakdown A US Engineering giant gave us data from Electrical trip unit data (48 Samples/Cycle and 4 Cycles prior and post events along with power data – voltage, current , frequency ) which was then analysed to spot significant differences in trip unit calibration which compromised asset integrity “Smelling” asset signals is again a recurring pattern encountered across industries Industrial industries are asset intensive. For every minute an asset is down millions of dollars are lost. Reducing down time of certain nodal assets is a use case which has a business case. Let’s take 2 examples we executed in this area to illustrate this theme 5 ©Fluturasolutions2015
  • 6. In process and discrete manufacturing industries, it’s very important to keep defects below a certain threshold. A new set of possibilities is being enabled from granular data collected from digital factories. It is the ability to dig deep into second level sensor data to understand specifics of process states which increased defect density. Let’s quickly take an example of a project we executed for a US based electrical product manufacturer. The product underwent a variety of operations and at each step of the operations sensors were monitoring viscosity, humidity, temperature data at second level and streaming it to SCADA based Historians. We were able to spot patterns using advanced machine learning techniques on a Spark based architecture which resulted in a 8 % reduction in defect density for the product 6 ©Fluturasolutions2015
  • 7. As the grid gets increasingly intertwined into all the assets, security becomes a very important consideration. Security forensics using granular event data can help investigators analyse sequence patterns exhibited prior to an adverse event happening. These digital signatures can be codified into a knowledge bank and watched in real time. From Flutura’s experience this is still in concept stage and pilots are being executed to solidify the analytical workflows which help a IOT security outcome. We will be happy to share some solid security use cases in the next 6 months 7 ©Fluturasolutions2015
  • 8. Pricing innovations using analytics is another area where we are seeing some powerful use cases blossom. For example, in the energy value chain trading happens in Energy exchanges and there is a lot of data generated from trades, competitive pricing information which needs to be mined to understand volatility patterns and to help time the market. Flutura’s energy data scientist are helping a major energy trade see those invisible pricing patterns to optimise millions of dollars by timing the market well by analysing past correlations Another use case which is finding momentum is dynamic asset pricing. Assets which are leased to customers (for example golf carts are equipped with sensors which record location, topple events, average cart speed, start, stop events). By analysing the granular usage statistics , asset leasing companies are able to have dynamic pricing of assets 8 ©Fluturasolutions2015
  • 9. We do agree that the marketing machines have been on steroids advocating IOT and Big Data as the panacea for everything. Industrial mindsets focus on tangible outcomes and some of the frequent questions we hear are Are they just fads or is it real ? Where is the business case for IOT big data in Engineering industries ? What are the use cases which are real for the Oil n Gas industry ? How can Retail energy providers and energy trading firms benefit from IOT and big data ? While a lot has been done on buzz word introduction, we felt the best way to make the case was to highlight tangible business outcomes which are tangible and "show them the money" As a startup we have been blessed as customers trusted us to unlock possibilities in their machine data and convert them into dollars. We hope you found the use case taxonomy useful and would love to hear your experiences from the trenches. As we say in Flutura May the big data renaissance awake every industrial organisation 9 ©Fluturasolutions2015