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Worm on the sensor: What happens when IoT data is bad?

Stephen Lawson | Dec. 19, 2016
Dirty devices at the edge sometimes send messy data to the cloud

Enterprises trying to use the internet of things already face a deluge of data and a dizzying array of ways to analyse it. But what happens if the information is wrong?

Bad data is common in IoT, and though it’s hard to get an estimate of how much information streaming in from connected devices can’t be used, a lot of people are thinking about the problem.

About 40 percent of all data from the edges of IoT networks is “spurious,” says Harel Kodesh, vice president of GE’s Predix software business and CTO of GE Digital. Much of that data isn’t wrong, just useless: duplicate information that employees accidently uploaded twice, or repetitive messages that idle machines send automatically. 

In addition, building a new IoT platform on top of old industrial reporting systems can cause problems because the legacy tools format data in their own way, Kodesh said. “You’re not taking the real, elemental data, you’re taking some translation of that.”

But sometimes devices just generate stuff that’s false or misleading.

Measuring the wrong thing

For example, if a worm crawls over a temperature and humidity sensor in a field, the farmer will get a reading on how warm and moist the worm is, which doesn’t help to run a farm. If a sensor gets covered with dirt or factory grime, or if it’s damaged by vandals, that can tweak the data it produces, too.

The harsher the surrounding conditions and the more isolated the device, the worse the bad-data problem is likely to be. In addition to agriculture, industries like oil and gas and energy distribution face this. But it’s not just far-flung sensors that have problems. Even in a hospital, a blood oxygen sensor clamped on a patient’s finger can start giving bad data if it gets bumped into the wrong position.

On top of that, some IoT devices malfunction on their own and start spewing out bad data, or stop reporting at all. In many other cases, human error is the culprit: The wrong settings mess up what the device generates.

One way to cut down on bad data is to make sure the gear is set correctly.

John Deere equips its giant farm tools with sensors that detect whether the machines are working right. The company’s ExactEmerge planter, which rolls behind a tractor planting seeds across a field, has three sensors per row of crops to detect how many seeds are being planted and at what rate. At least once a year, before planting time, the farmer or a Deere dealer will manually calibrate those sensors so they’re accurate, said Lane Arthur, Deere’s director of digital solutions.

 

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