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How Behavioral Analytics Is Changing Manufacturing, Transportation, and the Home

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How Behavioral Analytics Is Changing Manufacturing, Transportation, and the Home

In the future, every aspect of your product will generate data and use that data to change — and in many industries, this is already happening.

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Traditionally, data streams in from just a few places.

Maybe it’s user activity on your website. Maybe it’s an internal log of orders. The point is, to get a full picture of your company’s data you used to only have to link up a couple of databases.

But that’s all changing now. Valuable data is being generated not just on the web and mobile but also on IoT devices, bots, and more.

We’re moving toward a time where everything will be capable of transmitting data. In the future, every aspect of your product will generate data and use that data to change. In many industries, like manufacturing, transportation, and home technology, this is already happening.

Goodyear: The Intelligent Tire

Goodyear takes data collection seriously — so much so that its vision for the future looks more like a telematics company than a tire manufacturer.

That’s because IoT is changing the entire business model of Goodyear, moving it from a product-only company to a service-based one. Goodyear’s new programs range from simple tire modifications to moving beyond tires altogether.

On the simple end are initiatives like adding RFID (radio-frequency identification) tracking to their NASCAR racing tire in order to prevent thefts and improve the accuracy of inventory. However, location is far from the only information their tires are generating — sensors can measure temperature, tread depth, tire pressure, and more.

When this data is transmitted to the cloud and analyzed, it enables a new class of Goodyear tire services:

  • Improved vehicle control. Since braking and maneuvering on tires are dependent on weather factors, this information can be transmitted to the vehicle control system to improve handling.
  • Fewer tire surprises. Goodyear analytics can predict a tire blowout days in advance and notify the driver so that they can make informed decisions about when to get tires refilled or replaced.
  • Complete tire servicing. Since Goodyear is constantly ingesting data about tire health, they can take care of buying, fitting, maintaining, rotating, and replacing tires without any extra effort from the customer.

Goodyear is even offering services that have nothing to do with tires. Since they’re already selling telematics to vehicle fleets, they’ve also built value-added applications on top. For example, they have a driver scoring application that measures behavior like harsh braking and fast acceleration, which causes fuel inefficiency and vehicle wear.

Goodyear futuristic tire concept

The concept for the Goodyear tire of the future (Source: Motortrend)

And Goodyear isn’t stopping there. Their vision for the future is an AI-powered, spherical tire that can alter itself physically as it gathers information from its surroundings — like growing small dimples to increase friction if it senses a wet road.

This is the future of the manufacturing industry. Products won’t just be objects anymore — they’ll be data generating, data ingesting, and adaptable.

Southwest Airlines: Saving Millions on Fuel

For years, airlines have been using data on travel demand to determine which flights to offer between which cities. But to really analyze a flight, you need to know so much more than just how many passengers are on it — there’s fuel usage, temperature, turbulence, and so much more.

Southwest Airlines is now getting this sort of data through the industrial Internet, a digital network linking on-plane hardware like engines to the cloud. And one of the biggest opportunities this new data has provided is saving money on fuel.

Southwest Airlines runway takeoff

Source: GE

Southwest spends about $5 billion on fuel each year, meaning even a small improvement in efficiency can lead to some hefty payoffs. But so much of that fuel is wasted. In 2014, airlines altogether lost $4.3 billion in fuel just from idling on the tarmac. And since flights need to account for so many factors, they often carry a much larger fuel load than needed — the weight of which limits the number of passengers and amount of cargo a plane can hold.

But with their new streams of data, Southwest can get a much more precise understanding of how much fuel planes will need for different routes and weather conditions. The system also gives pilots in-air knowledge, so they can weigh the costs of dropping a few thousand feet to avoid turbulence.

Precise information on fuel needs helps optimize purchasing decisions, as well. Southwest planes fuel up at several locations, each with distinct pricing. Southwest analysts can make on-the-spot decisions about filling a plane up with extra fuel at a cheaper location.

All this data helps Southwest run a more efficient business and provide better customer service.

Other airlines, like Qantas, are starting to follow Southwest into this world of industrial Internet. This trend is likely to extend to the rest of the transportation industry as well: car services, delivery fleets, and cruise ships will all benefit from vehicles generating data which can be analyzed to cut gas and find the fastest and most fuel-efficient routes.

Neurio: Energy Monitoring for the Home

The idea of the smart home has been around since the early 2000s, but a lot of the technology released in this area has been more about convenience than actual intelligence. Thermostats you could change from your phone and DVRs you could record shows on from anywhere.

But now homes are producing data — and one of the major things it’s being used for is energy conservation.

Neurio launched its Kickstarter campaign in 2013 and started shipping products two years later. Its main hardware is a sensor box that is mounted in your home’s electrical breaker panel. Once installed (by an electrician), you get real-time stats on your home energy usage on the Neurio Home app. Neurio has Appliance Detection so you know exactly how much your dryer, bedroom light, and oven are costing you in watts (and dollars, once you input your utility company’s kWh rate). Using Neurio’s technology, homeowners know what behavior they should change to conserve energy and which appliances would be the most cost-effective to replace with a more efficient machine.

Neurio app screen capture

View of the Neurio Home application (Source: Techspot)

But Neurio isn’t stopping at just collecting data from your appliances. They’re also working on using that data to automatically lower your energy bill. They just introduced Storage Optimization Analytics, which can maximize savings for solar users.

Many solar utility companies have a Time of Use (TOU) system where they buy and store the extra energy produced by your home’s solar panels during the day and sell it back to you at night. The price of electricity varies throughout the day, rising during daytime hours when factories and other businesses need it. By considering a homeowner’s TOU bill, along with expected energy generation due to weather conditions and expected home energy usage throughout the day, Neurio decides to keep rather than sell this energy at various times of the day to minimize cost, while making sure the home battery has enough energy to handle the expected load.

Neurio’s expansion mirrors the transformation of home appliances as a whole — first, an appliance is connected to a larger network, then it collects data, and then it acts upon that data. The “smart home” is truly approaching.

Data Will Come From Everywhere

Even your garbage can is able to collect data now.

In the next decade, your company is going to have data streaming in from a huge number of sources. It’s vital to be able to easily pour this data into one location for a complete analysis. Imagine Goodyear just relying on logged maintenance calls and internal testing to find ways to improve their tires, rather than incorporating real-time data from tires on the road — not the situation they would want.

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Topics:
big data ,data analytics ,behavioral analytics

Published at DZone with permission of Archana Madhavan, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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