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How Machine Learning is applied in Industrial IoT

How Machine Learning is applied in Industrial IoT

Machine learning can have a greater impact on people’s lives when applied to the Industrial Internet of Things (IoT) than in consumer applications, according to a machine learning expert.

Speaking at the Strata Data Conference in Singapore earlier in December, vice president of data and analytics, Joshua Bloom, noted that when applied to the industrial IoT, machine learning can enable organisations to identify when an object should be replaced before it fails, or in the case of healthcare, help clinicians make sense of massive amounts of data in computer-assisted diagnosis.

Bloom said with 50 million industrial IoT devices expected to be deployed by 2020, the volume of data generated through those devices will also balloon to 600 zettabytes per year.

He said: “A single jet engine that GE creates produces about a terabyte of data in five hours.

“That’s an unfathomable amount of data coming from just one engine and with 50,000 flights a day, you’d realise the scale of the data that we’re starting to deal with.”

Bloom said organisations must also get comfortable with having false positives.

He said: “If you can live in a world with lots of false positives, you’ll do better than if you had no machine learning at all,”

He noted that this will ensure an “abundance of caution” built into machine learning models used in industrial applications.

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