The Internet of Things is filling the world with a flood of information. Making sense of it is another challenge. An IoT setup can easily produce the data that in a way will just swamp recipients unless they have systems that can manage the information.
Data collection has long been a critical success factor for businesses. Back in the 19th century, with an idea that would eventually lead to the use of computers in business, data was recorded on punch cards and the information could be analyzed with card counters and sorters. But the Internet of Everything creates far more data. The issue today is the need to process both the volume and speed of data generated by thousands, perhaps more, of devices that IoT contributes.
Consider an electricity producer’s field of windmill generators. They need to have rotors and blades set in the right place based on the behavior of wind. Checking the operation to review sensors used to require climbing 350 feet or so to get to the machinery. Today, instead sensors will collect the information and feed it all automatically back to the center, dispatching service to the top only when there is trouble. Furthermore, analytics technology will provide the operators with a flow of data, from regular reports on the windmills output to the most efficient plan for setting up service based on device needs and location. In some cases the feedback can even be sent in real time.
There are a number of steps needed to make the IoT analytics work. ABI Research found five clear steps in a study for the IEEE:
- Data integration collects and aggregates the streams of information.
- Data storage creates the implementation of management of information in data sets integrated for analysis.
- Core analysis runs information for an analytics engine to gain descriptive, predictive, and prescriptive results.
- Data presentation provides analytic insights through reports, visualization, and dashboard mash-ups.
- Professional services make it possible for external consultants to facilitate processes.
The issue today is the need to process both the volume and speed of data generated by thousands, perhaps more, of devices that IoT contributes.
Dealing with large information collections within business is nothing new. But the IoT formulas generate some deeper changes. And they generate a much larger collection, very quickly. In the old days, data was collected and sent off to the center for analysis. When possible, the first processing of information will be done where it is collected, cleaning and processing it at the site before it is passed on to higher-level analysis.
“Traditionally, to perform analytics, it required all data to be moved to a central location to be analyzed,” wrote Cisco vice-president Mike Flannagan. “In the IoT, with the amount of data being created in multiple places, moving data to a central location for analysis is difficult, expensive, and time-consuming. Together with our partners, we are creating solutions that involve doing edge analytics, without the need to move device data to a central place for analysis. The result? Organizations can improve their ability to make decisions quickly by doing the analyzing where the data is created.”
One example of IoT and analytics at work is a product called Powershelf by Panasonic. The need, as Panasonic puts it, “Today, everything seems to be smart and connected to the cloud: our phones, our watches, and even our refrigerators and thermostats. Somehow, price tags have been lost in the shuffle: locked in the same, paper-based, labor-intensive workflow that Mr. Whipple once used.”
The Powershelf replaces a standard label on the retail shelf that displays some basic information, such as price of units and cost per weight or quantity. But instead of a printed label, it is an electronic display and communication device. The Powershelf keeps track of the number of items leaving the shelf and can flag if the shelf needs restocking. The data center also can send out a price change and the new information goes both to the Powershelf and to the check-out. And you get helpful keys and instant information for business facilities, from warehouses for handling stock to the central office on how a given product sells.
IoT is a way to get critical information in the field, but analytics is often the needed measure to get the real benefit.
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IoT and Analytics: Real-Time Data Speeds Decision Making
Steve Wildstrom is a technology writer, analyst and consultant. He wrote BusinessWeek's Technology & You column from its creation in 1994 until BusinessWeek's acquisition by Bloomberg in December, 2009. Before starting Technology & You, Steve served as senior news editor in BusinessWeek's Washington bureau and edited the Washington Outlook column. Used with the permission of http://thenetwork.cisco.com/.
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