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Big data and IoT: Silent forerunners of transformation

Posted: 08 Jan 2015     Print Version  Bookmark and Share

Keywords:Consumer Electronics Association  big data  Internet of Things  sensor  CES 

Take your smartphone. It has between five and nine sensors inside, depending on the model, noted Dubravac. Hidden inside are a barometer, magnetometer, gyroscope, accelerometer, motion coprocessor and sensors that measure temperature, humidity, ambient light, proximity and sound.

"How much do you think all that high tech costs? The costs of all the sensors add up to under $5. Some obviously are more expensive than others, but the cheapest can be bought for as little as $0.07," Dubravac wrote.

In other words, it's now dirt-cheap to embed sensors. The result is a variety of IoT-enabled consumer devices including basketballs, weight scales, pacifiers and even crockpots.

The IoT revolution is an example of what Dubravac called "fragmented innovation," one where the economics of cheap technology has enabled data sharing to migrate from mass-market digital devices, primarily PCs, smartphones, tablets, to a growing assortment of products in highly fragmented consumer, business and industrial markets.

The future of big data

Dubravac, in his CES speech, listed several big data questions for 2015. What should we digitise next? How should we provide connectivity to these devices? Where should we embed and deploy sensors?

Trial and error will likely provide much of the guidance here, as manufacturers learn from the inevitable failures that come with early adoption of new technologies.

So what's really promising?

Driverless cars will be one of the IoT's most successful efforts, making their first appearance in cities within 10 years, predicted Dubravac. Connected vehicles will bring "a significant, if not total, decline of traffic and gridlock. Cars will move in unison with each other. As the human element is removed, so too are many of the barriers between data and decision," he wrote.

Data collection on a massive scale is kind of cool, but it also begs the question: Once all of this information is digitised, processed and analysed, how does it help us?

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