Dream team – IoT and AI
Author : Lee Hibbert, is an industry analyst at Technical Associates Group
11 October 2017
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The combination of the Internet of Things with rapidly-advancing Artificial Intelligence technologies will allow manufacturers to make the most of big data. Lee Hibbert, industry analyst at Technical Associates Group discusses his thoughts.
The era of the smart factory is upon us. Cheaper and more reliable connectivity is enabling manufacturers to embrace Internet of Things-enabled architectures, giving them far better visibility of their factory assets than ever before.
In an industrial context, the connected ‘things’ can be a long list of systems and machines that can be fitted with sensors which record data around pressure, level, flow, temperature, vibration and acoustics. This data, combined with sophisticated analytics, can be used to reveal patterns and problems within factories, or with equipment out in the field.
But there’s a problem. As companies rush to adopt IoT, they fit more sensors and create more data. Soon, it becomes difficult to manage, analyse and create meaningful insight from the information that’s been collated. In time, these ever-increasing data flows can become totally overwhelming.
That’s where artificial intelligence (AI) comes in. By enabling truly smart machines, which can simulate intelligent behaviour and make well-informed decisions with little or no human intervention, it becomes possible to unlock the value from large volumes of digital data. For some, this combination of IoT with AI is the holy grail for industry: it’s the only way of improving the speed and accuracy of big data analysis, providing true insight into what’s working well or what’s not.
According to IBM, AI and IoT are shaping up to be a symbiotic pairing, as AI doesn’t just depend upon large data inputs; it thrives upon them. “AI systems can rapidly consume vast quantities of structured and unstructured data, and give it meaning by creating models of entities and concepts, and the relationships among them,” says Susanne Hupfer, a senior consultant and lead analyst at IBM. “They generate hypotheses, formulate possible answers to questions, and provide predictions and recommendations, which can be used to augment human intelligence and decision making.”
Furthermore, given new data and scenarios, AI-based cognitive systems evolve and improve over time, inferring new knowledge without being explicitly programmed to do so. As Hupfer at IBM notes: “Got vast volumes of data from IoT? Feed it to AI systems and let them make sense of it.”
Industry seeks benefit of AI
The potential of AI as an enabler of smart factories and products is a cause of huge excitement within the research and development divisions of the big industrial players. One company that is betting the house on AI transforming its business is Siemens. The German giant has more than 200 experts working on data analytics and neural networks, identifying a wide variety of applications in areas such as energy distribution, electric motors, and rail technology. It believes that AI will change the way that companies make products, and how equipment is used out in the field.
Siemens says that the potential impact of AI within cannot be over-stated. In a recent presentation, Roland Busch, Siemens’ chief technology officer, explained how the company was already using AI to improve the operation of gas turbines. By learning from operating conditions and other data, Busch said AI could help achieve a significant reduction in the emission of toxic nitrogen oxides without affecting the performance of the turbine or shortening its service life.
Lee Hibbert, is an industry analyst at Technical Associates Group
Busch said that the application of AI was not restricted to new products. Siemens is also looking at how it can be retrofitted to existing equipment such as motors and transmissions, bringing them into the digital age. Here, smart boxes containing sensors and a communications interface can be used to analyse data, with AI systems then drawing conclusions regarding a machine’s condition. This information can be used to underpin predictive maintenance programmes.
Siemens is not alone. Arch-rival GE is also throwing millions of dollars at AI research and development, looking for ways to apply AI to jet engines, medical scanners and other machines. There’s particular scope for such technologies within the smart factories of the future, predicts GE. AI systems could, for example, provide workers with the intelligence they need to make informed decisions around whether to scrap or repair a turbine blade. The data used to underpin such decision making could also be simultaneously collected in a closed loop to make the system smarter and smarter, so next time around it provides even better insights.
AI – where next?
Given the scale and range of potential benefits on offer, it’s hardly surprising that companies in many industries are beginning to take steps to seize the opportunities presented by combining IoT and AI. According to a research note published by international consultancy PwC, IoT/AI will make an impact across manufacturing – in markets as diverse as domestic appliances, aircraft, automobiles, ships and mining. The document - Leveraging the Upcoming Disruptions from AI and IoT – the combined disruption from AI and IoT will reshape our business life in a dramatic manner that is not fully imaginable or comprehensible by most companies today.
“At one end of the scale, it will displace routine, monotonous human jobs with machines,” says PwC. “At the other, it will radically disrupt the competitive landscape, by giving the early adopters of AI tremendous advantages in terms of lower costs and a head-start in pursuing new business opportunities.”
While the full impacts of this disruption will not arise overnight, they will come a lot faster and sooner than most businesses and individuals are currently expecting, PwC insists. So, smart companies are not waiting for the tsunami of disruption to reach their shores before they react. Instead, they are moving now to start the strategic dialogue needed to fully understand and prepare for the disruptions before they arrive.
“Companies that take this proactive, far-sighted approach can turn the upcoming disruptions from an irresistible force that could sweep them away, into a massive opportunity that they’re well-placed to realise. Put simply, the AI revolution is here — and now is the time to get ready for it,” it concludes.
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