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Business use of internet-connected devices is catching up with consumer usage, according to Gartner’s latest forecast.
The consumer segment is the largest user of connected things with 5.2 billion units in 2017, which represents 63% of the overall number of applications in use, Gartner estimated. Businesses are on pace to use 3.1 billion connected things in 2017.
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In addition to smart meters, applications tailored to specific industry verticals – including manufacturing field devices, process sensors for electrical generating plants and real-time location devices for healthcare – will drive the use of connected things among businesses through 2017, with 1.6 billion units deployed.
Speaking to Computer Weekly, Gartner research vice-president Bettina Tratz-Ryan said: “We see a strong use of the internet of things [IoT] in manufacturing and industry 4.0 applications.”
The market for vertical IoT applications in business is forecast to grow by $189bn to $866 bn by 2020.
Tratz-Ryan said IoT creates visibility into industrial processes, with this data captured using IoT platforms. Gartner expects IoT platform usage to grow as more industrial IoT applications are deployed.
“The platform market will increase, as will services relating to identity and access management,” she added.
Tratz-Ryan believes companies such as HPE and IBM will focus on becoming providers of IoT platforms.
At the same time, the major industrial firms, such as GE and Siemens, which previously invested in their own proprietary systems to run industrial machines, are set to become more open.
“They are realising that only an ecosystem can work [for successful IoT],” said Tratz-Ryan. “Industrial companies have to become more open as they will not be able to integrate the diversity of industrial business applications into their own platforms.”
While major companies may be considered to have deep domain expertise, this differentiator is likely to come under pressure as they grow their ecosystems and more companies join in.
Tratz-Ryan said: “There is a race of expertise versus scale. Traditional industrial companies have the expertise but they will be required to be much more agile. Leaders in this market will understand specific industrial environments and the context of where the data being generated is used.”
Deep learning and artificial intelligence (AI) could help industrial companies scale their platforms, making them more agile and able to deal with very specific customer requirements.
Tratz-Ryan predicted deep learning could be applied to customise orders. For instance, an industrial company would be able to understand the reason a particular raw material is being purchased, which would then enable it to offer individualised product manufacturing.