Forbes, Jason Hope Point to Big Data Mistake in Industrial IoT

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At the heart of what drives the Internet of Things is data, yet in some industries, like industrial manufacturing, that data is not as accessible as one might think. Industrial manufacturing equipment, which is decades old, is lacking the accessible data necessary to make the Internet of Things helpful, Jason Hope and Forbes agree.

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Apps must have all of the data available. With industrial equipment, much of which was put into use 20 to 30 years ago, you have a pile of data lost somewhere in the IT or maintenance department.

The Internet of Things holds great potential in cataloguing and analyzing big data to make predictions about future actions of devices and consumer behavior, but Forbes and Jason Hope believe that there is one glaring mistake in the industrial sector. While the connectivity provided by the Internet of Things holds great potential in analyzing streaming data from industrial machinery, to help predict future performance and maintenance needs, and that is getting access to the data in the first place.

According to the January 27 article by Adrian Bridgwater entitled "The Big Data Mistake in the Internet of Things," designers are working to use the Internet of Things to predict the behavior of machines. John Bates, the global head of industry solutions at Software AG, was quoted as saying "With cloud hosted analytics and algorithms that are accessible by digital sensors and devices, actions like process updates, events responses and machine behavior can then be implemented. The key . . . is the ability to rapidly build apps that tap into, analyze and make smart decisions on big data."

Yet Bridgwater and Jason Hope argue this is not the ultimate key. "In order to analyze and make decisions from big data," warns Hope, "Apps must have all of the data available. With industrial equipment, much of which was put into use 20 to 30 years ago, you have a pile of data lost somewhere in the IT or maintenance department. That data is not accessible to the latest generation of Internet of Things devices."

What is the answer to this problem? One answer is to find technology that will organize and aggregate that data into something usable by modern analytics. Another solution is to simply wait until more data is generated by the newer generation of machines that are equipped with Internet of Things connected sensors.

As the Internet of Things continues to grow, developers will need to address all of the issues that arise, including hard-to-access data such as this.

"The potential benefit of the Internet of Things in the manufacturing sector to predict machine behavior, failure rates and maintenance needs is incredible," says Hope. "The key will be to gain access to this older data, so predictive apps and devices can have a full range of data with which to make predictions."

About Jason Hope

Jason Hope serves the Arizona community through his work as an entrepreneur and futurist. He has a passion to watch the development of the Internet of Things, which he believes will make the future easier. Learn more about his work and current projects at http://www.jasonhope.com.

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