Siemens Digital Industries Software and SAS announced a new partnership that will help companies create new IoT edge and cloud-enabled solutions by applying SAS and open source streaming analytics through Siemens’ MindSphere. Users will gain access to SAS advanced and predictive analytics in MindSphere, which can accelerate the adoption of machine learning (ML) and artificial intelligence (AI) in Internet of Things (IoT) environments.
Siemens and SAS will collaborate to engage with new and existing customers and, beginning with streaming analytics, enable near-real-time embedded AI for IoT devices at the edge. The partners expect the solutions to be generally available later this year. Earlier in the year, Siemens announced a partnership with Litmus Automation on IoT edge computing.
"We are excited to leverage their analytics in MindSphere,” said Stephen Bashada, executive vice president and general manager of Siemens MindSphere. "The combination of Siemens’ deep industrial domain knowledge with SAS’ deep analytics knowledge is a powerful step forward for IoT."
By applying AI and operationalizing its potential at scale, the partnership hopes to drive an end-to-end solution framework. Companies currently using both SAS and MindSphere will be able to port and deploy previously developed SAS models natively into MindSphere.
Siemens’ MindSphere is the cloud-based, open IoT operating system that connects real things to the digital world through open connectivity. MindSphere also enables a partner ecosystem to develop and deliver new applications providing a basis for new business models. With its APIs, MindSphere applications can be quickly developed by Siemens, its partners or directly by customers. In combination with Siemens’ approach to holistic digital twins, companies can leverage MindSphere to close the loop through product ideation, realization and utilization to integrate IoT data throughout the value chain.
SAS advanced analytics algorithms capture and analyze large amounts of data gathered from industrial control systems and converge IT and OT worlds by using derived actionable insights to drive intelligent operational and business processes. SAS’ investment in IoT analytic open source compatibility allows data scientists to code in their language of choice while relying on the scalability of SAS.
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