4 Major Trends in IoT Analytics in 2023
From enhanced digital twin tech to the rise of computer vision, here are some key trends expected in the new year.
Over the years, analytics has become an integral part of IoT. Industrial organizations such as manufacturers, as well as transportation and energy companies, and governments worldwide, continue to embrace these technologies to enhance operational efficiency and enable significant cost and operational savings.
Advanced analytics like artificial intelligence (AI), streaming analytics and machine learning (ML), when combined with IoT technologies and sensors, can help power smart factories, grid infrastructure and even cities. But what will 2023 bring in this important area? IoT World Today spoke to Jason Mann, vice president of analytics company SAS about the rise of this technology, and the trends predicted to emerge.
The Rise of Analytics in IoT
According to Mann, four major trends will emerge in IoT analytics over the next year: the rise of low-code and no-code automated machine learning (AutoML), enhanced digital twin technologies, industrial adoption of computer vision (CV), and a blurring of the lines between edge and cloud. These trends don’t mark a departure from previous years, but rather a continuation of market trajectories following the pandemic.
Specifically, in 2023 SAS predicts there will be greater availability of industrialized AI through low-code and no-code AutoML, with these models provided through self-service marketplaces and with the possibility of being enhanced with packaged services for customization and deployment.
Mann says we’ll also see more purpose-built digital-twin applications in 2023 specialized for defined use cases in energy, infrastructure optimization and industrial manufacturing sectors. Organizations are also expected to increasingly adopt CV and other AI technologies, with the kinds of industries harnessing these technologies expanding beyond more niche use cases by IT staff and data scientists. According to Mann, CV initiatives will focus on “yield improvement, operational efficiency and safety.”
Finally, with cloud hyperscalers like Microsoft Azure, Amazon Web Services and Google Cloud Platform starting to roll out core cloud services on the edge, edge computing will become an extension of cloud computing. Workloads will be distributed intelligently across hybrid environments. This will mean quicker adoption of IoT analytics at the edge in 2023 to enhance decision making at the source.
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