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Levelling up IoT with AI

Nurdianah Md Nur
Nurdianah Md Nur • 5 min read
Levelling up IoT with AI
Combining AI with IoT enables huge volumes of streaming data from IoT sensors and edge devices into better, faster decisions. Photo: Shutterstock
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According to International Data Corp, Asia Pacific (Apac) is expected to spend US$435 billion ($586 billion) in 2027 on the Internet of Things (IoT) as organisations and cities race to become more connected.

The drive to enhance product and service quality, efficacy and customer experience is fueling investments in IoT. Yet, for Apac organisations to fully unlock these benefits, leveraging artificial intelligence (AI) alongside IoT is essential.

In the human body analogy, IoT without AI is akin to having five senses without a brain. We can perceive sights, sounds, smells, tastes and touches, but without intelligence, we can’t interpret and act on that information effectively.

“By combining AI with IoT, organisations can transform huge volumes of streaming data from IoT sensors and edge devices into better, faster decisions. As a result, they can optimise performance, reduce energy costs and greenhouse gas emissions, enhance worker safety, improve equipment maintenance, ease traffic problems, mitigate flood risk and much more,” says Jason Mann, vice president of IoT at SAS, a data and AI platform provider. He also shares with DigitalEdge a real-world use case and how generative AI will democratise access to AI for all to enable smarter, connected operations.

Jason Mann at SAS Innovate 2024 in Las Vegas. Photo: SAS 

See also: Sun Singapore to deploy AI-based parking solution powered by AMD

Could you share an example of how a company creatively combines IoT, AI and analytics to reach their business objectives?

A wonderful example of sustainable manufacturing through AI and IoT analytics comes from Austria-based Wienerberger, a provider of innovative, ecological solutions for the entire building envelope. The company has facilities throughout Europe and North America and, since 2009, has a state-of-the-art plant in India.

Wienerberger was searching for ways to optimise its operations and be more sustainable. Like many organisations, it experienced instability in global energy markets, such as wildly fluctuating natural gas prices, due to the global geopolitical situation. The company needed better ways to reduce energy consumption since many of its factories are powered by natural gas.

See also: Redefining Asean’s manufacturing landscape with deep learning

Weinberger turned to SAS Viya (SAS’ cloud-native, massively parallel data and AI platform) running on Microsoft Azure cloud and SAS Analytics for IoT to power a digital twin of its factory operations. This helps Wienerberger optimise its manufacturing process while lowering its use of natural gas, reducing greenhouse emissions and improving product quality.

With SAS, Wienerberger can collect data from various sources, from IoT edge devices and sensors throughout its manufacturing facilities to environmental data on weather and humidity to product spot checks during and after production. All this data reveals fluctuations that can lead to inefficiencies and unnecessary energy use.

The company’s initial savings in a pilot plant in Poland in 2022 were around 9%. Today, its savings are 15% of specific energy consumption. Weinberger is turning its brick plants into data-driven factories by reducing energy consumption and CO2 emissions while maintaining or improving quality and yield. It is looking to roll out the SAS-powered solution to its 200 facilities worldwide.

What are the common mistakes Apac organisations make when embracing AI and IoT?

Too many organisations in Apac still consider AI, IoT and advanced analytics to be the domain of quantitative experts and data scientists. This is no longer the case.

For instance, generative AI and large language models, such as OpenAI’s ChatGPT and SAS’s Viya Co-Pilots, represent innovative advancements in an age-old concept. Over the decades, organisations have utilised models to generate analytical insights, refine processes, amplify outcomes, and inform strategic business choices.

Generative AI has particularly sparked interest by democratising access to these technologies, catering to diverse job roles and levels of expertise.In an industrial setting, operators and front-line workers can use generative AI to ask questions like “What is my biggest area of concern on line 3?” and “Where are we seeing the most areas of failure in operation B?” Then, the answers will be acted upon in real time to minimise the impact. This engagement with data and AI at a conversational level can deliver real-time insights and better operational decision-making.

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In the heavy industrial space, for example, one of our customers was looking to expedite time-to-resolution for issues that arose on the manufacturing line. Historically, if a machine threw an error code, the customer would have to go to one system to see what the code meant, another system to see how to repair it and a third system to look at how this issue had been treated in the past. With generative AI, they can combine all that data and give operators one interface to evaluate, assess and solve issues quickly and effectively.

How is SAS helping organisations harness the power of AI for IoT and other parts of their business?

With generative AI, we’re entering a new era of human-machine interaction, where that interaction is becoming conversational, either through text or audio. AI is now a collaborative partner that augments human productivity.

In April, we announced at SAS Innovate two new generative AI offerings (currently available in private preview) and expanded the generative AI capabilities of another:

Viya Copilot enhances productivity for developers, data scientists and business users with a personal assistant that accelerates analytical, business and industry tasks. Viya Copilot offers diverse tools for tasks like code generation, data cleansing, data exploration, marketing planning, journey design and knowledge gap analysis.

SAS Data Maker addresses data privacy and scarcity challenges by generating high-quality synthetic data without compromising sensitive information.

SAS Customer Intelligence 360 already offers generative AI assistance in streamlining marketing planning, journey design, content and creative development. We’re now introducing three new capabilities: using generative AI to build recommended audiences based on natural language prompts, a chat experience to interpret audience data and a generative AI suggestion service for email subject lines.

These new capabilities, combined with SAS data and AI platform SAS Viya, allow organisations to effectively use generative AI to transform raw data into real-time insights that propel their business forward.

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