Four predictions from tech giant IBM on the future of the Internet of Things in 2018

Despite some questionable uses (looking at you, smart toaster), the Internet of Things (IoT) has continued to be a strong area of development and innovation in the tech world. One only needs to look at the offering from this year’s Consumer Electronics Conference (CES) to see the widespread use of the technology.

More than 11 billion IoT devices are predicted to be in the world in 2018, and established companies and startups alike are looking to the tech to bring on further innovation. One of these businesses, Australian IoT startup Thinxtra, received $10 million in funding last year to develop its long-range IoT transmission hardware, which it’s aiming to implement in a range of industries and businesses.

Bret Greenstein, vice president of tech giant IBM’s Watson IoT Consumer Business division, recently spoke to Forbes about four key trends he could see changing the way IoT functions and integrates, operating mainly around its integration with other emerging technology.

Here’s what he thinks will be big in IoT over 2018.

1. AI will make it smarter

Artificial intelligence seems to be being thrown into pitch decks and innovation strategies left right and centre, so much so Cognitive Finance Group founder Clara Durodie told a panel last year her VC firm will be looking for investment in “real” AI, “not just for the sake of marketing or selling, and not just AI on a business plan”.

Integration with that sort of AI could see IoT systems better understanding humans and each other, says Greenstein, given developers start to understand how best to use it.

“In the early days you could do IoT in your home in a lot of different ways and there were a lot of wires and a lot of hard-code — mobile apps came later, but it was still an isolated experience that doesn’t really feel connected,” Greenstein told Forbes.

“AI is helping to bridge that gap — now we are seeing automakers and hotels and other companies trying to create more integrated experiences and using AI to better understand and interact with people.”

2. More power at the “edge”

Greenstein also predicts that front-facing parts of systems, such as cameras and microphones, will have more processing power pushed towards them and given more functionality.

“Suddenly there are cameras that can not only see, they can understand the image, and microphones which can listen — that’s increasingly being pushed to the edge,” he said.

This also cuts down on redundant data being sent back to the cloud, allowing systems to better process incoming information and leading to improved privacy for users. Greenstein explains using an example of a home security system detecting when residents are in danger:

“In this scenario, you might use cameras to tell if someone is recovering well, if their gait is normal or they are walking a little slower than they should be. But also you can pick up sounds like breaking glass, things falling or water spilling. And because the processing is done at the edge, we maintain privacy because nothing is sent to the cloud unless something bad happens,” he said.

3. Blockchain’s back, baby

Just in case you weren’t already inundated with buzzwords and new-concept business ideas, Greenstein claims blockchain’s immutable distributed ledger technology is well-suited to slot into IoT systems.

IBM currently runs its own blockchain solution through the Linux Foundation’s HyperLedger, which Greenstein says will have a number of partnerships to announce over 2018.

“What people missed about blockchain, because they were so focused on the financial side of things, which is the obvious use case, is that all of this IoT data, particularly in supply chains or where things move between owners, requires all of that data to be stored in some kind of unchangeable record,” he told Forbes.

4. Bright spots in manufacturing and industry

“There’s no question the industrial side of IoT is growing rapidly. [At first] everyone thought it was about the sensors — but we’re getting to the point where it’s the insights and interactions with people,” Greenstein said.

“In a way, it’s kind of supercharging manufacturing operators and people who do maintenance on machines by providing real-time data and real-time insights.”

Greenstein demonstrates the use of these insights through things like automated technical manuals being fed information from IoT systems and interpreted by AI.

“People ask a question — they don’t have to look through the manual anymore. They can ask their manual, ‘is this the right setting for the tyre pressure’,” he says.

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