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Companies use machine learning to enable predictive maintenance, optimisation of connected machines.
AT&T on Tuesday took the wraps off a new IoT analytics solution that uses IBM’s Watson machine learning technology to give enterprises actionable insights into the performance of their connected machines.
The pilot collaboration analyses and presents data harvested from AT&T’s various IoT management solutions, including M2X, Flow Designer and Control Centre. It also gathers information from IBM’s Watson IoT portfolio for connecting, building, launching and managing IoT apps and devices, as well as IBM’s machine learning service, and the Watson Data Platform – a data ingestion engine equipped with cognitive decision making.
AT&T said its new service enables companies to better utilise their own generated IoT data to enable predictive maintenance and optimisation. For example, an oil and gas company that wants to detect anomalous events within its wells could use it to create models that help predict potential failures or machine malfunctions.
"Businesses are eager for actionable insights from their connected devices that help improve their processes and take the guesswork out of decision making," said Chris Penrose, president of IoT solutions at AT&T. "Integrating the IBM Watson Data Platform into our IoT capabilities will be huge for our enterprise customers."
Tuesday’s announcement follows on from the agreement that AT&T and IBM struck in July 2016 to combine their IoT platforms.
"As part of our continued collaboration to drive innovation, IBM is working with AT&T to combine our strengths and expertise to combine analytics solutions on the IBM Cloud that will enable AT&T’s enterprise customers to utilise their complex data in a meaningful way and deliver insights that can help accelerate their business transformation," said Steve Canepa, general manager of telecommunications, media and entertainment at IBM.
