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From SCDigest's OnTarget e-Magazine

- March 10, 2015 -

RFID and AIDC News: The Five Types of Data in the Internet of Things

Industrial Applications for IOT Leading the Way, though Information Logistics will be Key to Success

SCDigest Editorial Staff

The Internet of Things (IOT) seems to reaching super hype speed right now. Whether that will lead to IOT later falling into what Gartner has called the "trough of disillusionment" remains to be seen, though Gartner would say the track record makes that highly likely.

SCDigest Says:

A huge emerging issue in all of this is that it turns out there are very few data standards yet for internet of things applications.

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Regardless, a lot of companies are putting a lot of dollars into IOT research and applications - interestingly, especially industrial companies - therefore giving IOT in those cases some clear connection to the supply chain, though how that will play out in practice remains to be seen.

As an example of the efforts by industrial companies, giant GE a few years ago opened a massive software center about 30 miles east of San Francisco. The company says it is now able to capture billions of data points from 10 million sensors installed on $1 trillion worth of its equipment, and it has already notched more than $1.1 billion in annual revenue from the various software and data products developed there. For example, it offers data relative to predictive maintenance and other operational issues on GE aircraft engine sold to airlines around the world.

All of this of course is already creating and collecting massive amounts of data. That in turns leads inevitably to what might be dubbed "information logistics" - rules and decisions about what data from IOT applications is to be sent where.

An easy example: if a pallet of refrigerated food has a sensor to monitor ambient temperature, how often should that internet connected sensor send up its data to some repository in the Cloud? Every 10 minutes? Every half hour? Only when the temperature changes by some predefined level?

These are the types of questions that business and often supply chain professionals will have to grapple with as IOT-based systems are designed and deployed. Indeed, it will likely take a partnership of IT, supply chain and marketing at minimum to developed IOT-based solutions, with marketing playing a key role because as with the GE example, the goal for industrial companies will usually be to developed new products and services that can be sold to customers.

Who will "own" the IOT systems when deployed often remains an open question.

(RFID and AIDC Story Continued Below)

CATEGORY SPONSOR: SOFTEON

The Five Levels of IOT Data

With that backdrop, SCDigest believes a framework for considering the types or levels of IOT-related data could be useful. We propose the following:

Level 1: The data collected by IOT-connected devices, usually through sensors. This would involve of course the identity/serial number of thing (machine, pallet, etc.), and other attributes such as location, temperature, humidity, operating data, etc.

Level 2: The subset of that data sent on to a data repository: Some but usually not all of the data collected, as described above, will be sent on to a data repository - often but not always in the Cloud. Again, there will be many, many questions here, such as what data needs to be sent where, is it sent in real-time or in batches, and more. A key factor will then in turn be how much memory the chip connected to whatever the "thing" is has available.

Level 3: The collection of that data from millions or billions of individual IOT-generated date feeds into a data repository, Cloud-based or not.

Level 4: General reporting based off that consolidated database, e.g., how many machines are in the field, how many are operating, what is their utilization and hundreds of other reports.

Level 5: Use of this database information for advanced analytics applications to provide even greater, generally non-obvious insight into what is happening and why across some group of things in the field. This will often involve what are called predictive analytics, and what GE is doing with its aircraft engines seems to fall into this category.

As another example of level 5, freight carrier Werner used data from IOT-systems on its trucks to better understand what driver behaviors were associated with on-the-road accidents. Again, there will be dozens or even hundreds of these potential applications - some for a company deploying IOT systems own benefit, some designed for customers either to simply add value to a product or wrapped in a separate service.

A huge emerging issue in all of this is that it turns out there are very few data standards yet for internet of things applications. Consider, for example, the way GS1 standards connect a company identifier to a serialized carton of goods, so that the same serial number can be used by multiple manufacturers.

SCDigest research does not show that any such standards have yet been developed for the IOT, though different data communication standards are emerging. More on that soon.

What do you think of our 5 levels of IOT data? What would you add or change? Let us know your thoughts at the Feedback section below.

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