How IoT Will Change Big Data Analytics
Updated · Nov 17, 2014
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What do SAS, Cisco, Duke Energy and AT&T have in common? They are all big proponents of the Internet of Things (IoT), also often called the Industrial Internet.
The central idea behind IoT is that sensors and microchips can be placed anywhere and everywhere to create a collective network that connects devices and generates data. Instead of that data sitting in an information silo where it is accessible to only a few specialists, it becomes part of a Big Data “lake” where it can be analyzed in the context of other information.
“The Internet of Things means everything will have an IP address,” said Jim Davis, executive vice president and chief marketing officer, SAS.
He laid out the value proposition for oil rigs which generate eight terabytes of data per day. IoT could open the door to greater productivity and more effective predictive maintenance. If something breaks down, it can lead to millions in losses. By placing sensors on rigs and monitoring them, it is possible to better understand what’s happening and keep the equipment running.
“Due to the advances in Big Data and analytics, we can now afford to store and analyze the data associated with IoT,” Davis said.
Yet the Internet of Things will also require companies to reconsider how they use Big Data and to ensure they have the appropriate infrastructures in place to leverage it.
IoT and the Power Grid
Duke Energy is one of the largest utilities in North America, with assets spanning coal, nuclear, natural gas and renewables. Jason Handley, director of Smart Grid Technology and Operations, Emerging Technology Office, Duke Energy, is enthusiastic about the concept that anything can be connected with anything else – buildings, vehicles, people, animals, power generation assets or utility consumers (via smart meters).
“More sensors are the DNA roadmap to allow unrelated things to talk,” said Handley. “They will have embedded microprocessors which are always on.”
The potential he sees should be viewed in the context of the smart grid. Instead of power plants producing the power they think will be needed, and individual households and businesses consuming that power independently, smart meters will enable users to program their own consumption to avoid peak pricing rates, prevent certain devices operating at specific times, and provide the grid operator with far more data (and perhaps limited control) so they can more closely anticipate demand.
“We will be able to partner with customers to create energy usage profiles that meet their needs,” said Handley. “For the good of the power grid, some customers may even let us have limited control over high usage devices in their buildings.”
The goal is to establish the lowest cost and highest quality grid possible. This will be enabled by a distributed intelligence platform that harnesses analytics to sift through data that streams in from every user. But it won’t be a one-way street. The user can also gain trending data and usage reports and program his/her building as a means of containing cost.
“The result will be a distributed intelligence platform with progressively more intelligence on premise, at the substation and in the central hub,” Handley said.
Not All IoT Data Is Important
Mobeen Khan, executive director of Product Marketing Management at AT&T, can also see the potential of the Internet of Things. His company is beginning to harness it to read alarms across the entire land line and cellular network, and to attain better control and optimization of field services.
A key challenge with IoT, he believes, is data management: determining what type of data is important, what should be transmitted immediately, what should be stored and for how long, and what information should be discarded. Otherwise, you could end up with an almost infinite pile of data to analyze, when only a relatively small portion is of real importance.
“Some data just needs to be read and thrown away,” Khan said.
IoT and Autonomous Vehicles
When you take IoT into the realm of intelligent vehicles, the amount of data begins to boggle the mind. But the upside is potentially colossal.
“The Internet of Things helps us to connect your vehicle to other vehicles, as well as traffic lights and parking spaces, which can add up to no more traffic jams, fewer red lights and no need to drive the vehicle,” said Andreas Mai, director of Smart Connected Vehicles, Cisco Systems. “Having autonomous cars which drive themselves would eliminate 80 percent of crash scenarios.”
Cisco estimates $19 trillion in economic benefits over the next decade from IoT-related improvements. For example, each vehicle might yield $1,400 per year in savings on fuel and other expenses, said Mai. Such a change would obviously disrupt industries such as automotive, insurance and public transport, as it would fundamentally shift the way they do business.
On the data side, Mai urged IT organizations to get ready to deal with far larger amounts of data. That demands the building of a more scalable infrastructure and greater employment of analytics.
“Big Data is the fuel of the connected vehicle,” Mai said. “It is analytics which gives you the true value.”
Google has been driving autonomous networked vehicles around the U.S. for some time. Another project is ongoing in Michigan where 3,000 such vehicles are involved in a pilot project. When you scale it up to every vehicle, traffic jams would shift from the roadways to the airwaves.
IoT Infrastructure Changes
It is unrealistic to expect satellite, cellular or cloud-based networks to be able to cope. Mai said the amount of data already flying around global networks is already overwhelming telecom networks. His solution is to supplement cellular networks and the cloud with additional networking from what he termed “the fog.” This is, in essence, a localized network that supplements the cloud, satellite and landline systems, perhaps only operating in the vicinity of one junction.
“It isn’t possible for cars to receive external impulses from traffic lights, mapping programs and other vehicles if it all has to go via the cloud,” said Mai. “So the IoT will require a lot more compute power on the edge of the network.”
But this also poses tremendous problems in the realms of Big Data and analytics. Where is this data going to be stored? How is it going to be pooled? Where will the analysis be done? Obviously, the vehicles will become smarter, more able to retain larger amounts of data and perhaps able to perform limited analytics. But that won’t be enough.
“Every enterprise needs to factor in how the Internet of Things is going to affect them and their business, and must respond by establishing the right infrastructure to support this level of Big Data and analytics,” said Mai. “If they don’t, they will fall behind.”
Drew Robb is a freelance writer specializing in technology and engineering. Currently living in Florida, he is originally from Scotland, where he received a degree in geology and geography from the University of Strathclyde. He is the author of Server Disk Management in a Windows Environment (CRC Press).
Drew Robb is a writer who has been writing about IT, engineering, and other topics. Originating from Scotland, he currently resides in Florida. Highly skilled in rapid prototyping innovative and reliable systems. He has been an editor and professional writer full-time for more than 20 years. He works as a freelancer at Enterprise Apps Today, CIO Insight and other IT publications. He is also an editor-in chief of an international engineering journal. He enjoys solving data problems and learning abstractions that will allow for better infrastructure.