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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 toONE POWERFUL UNANSWERED QUESTIONWhat are some of the measurable outcomes impacted by IOT use cases ?So here they come ...

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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

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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 intervalsThis 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.

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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 breakdownA 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

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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

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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

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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’senergy 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 correlationsAnother 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

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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

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