• Enables more effective, responsive and agile decision making for Industry 4.0 segments by processing OT data closest to the source.
• Building on Nokia DAC private wireless and Nokia MX Industrial Edge, MX Grid micro-edges deliver the industry’s first hyperconnected decentralized AI/ML processing platform.
• Enables implementation of a wide range of mission- and life-critical industrial applications, including predictive maintenance, security and surveillance, worker safety, tracking and positioning, and quality assurance.

Espoo, Finland – Nokia today launched MX Grid, the world’s first on-premise, hyper interconnected and distributed AI/ML solution that enables organizations to improve OT responsiveness and decision-making by processing and analyzing data closest to the source.

As part of the Nokia one platform, MX Grid accelerates Industry 4.0 adoption, building on the Nokia MX Industrial Edge (MXIE) platform and leveraging reliable wireless connectivity, to offer a new OT data processing architecture that facilitates IT/OT convergence, supporting mission- and life-critical industrial applications.

A recent report by Omdia highlights the growing industrial trend of data pre-processing at the edge to improve productivity, efficiency and agility, which requires processing power located in or near the device (including ML and AI). Newly connected nodes with converged functionalities show the highest global growth rate (CAGR 2022-2027: 11.3%), driving industrial digitalization and IT/OT convergence.

Today most AI/ML assets run in cloud environments. With MXIE, Nokia introduced OT compliant AI/ML processing capabilities on-premises, whereas MX Grid brings this capability even closer to the OT data source. MX Grid leverages a pool of orchestrated compute capable field devices – known as ‘micro-edges’ – with a specialized, AI-capable software stack. These micro-edges are connected by private wireless networks and/or reliable Wi-Fi using MX Boost, which augments both technologies.

MX Grid enhances the efficiency of enterprise OT operations using decentralized workload processing and real-time, agile decision-making, bringing intelligence to legacy OT assets. The solution enables a more effective implementation of a wide range of mission- and life-critical industrial applications, including predictive maintenance, security and surveillance, worker safety, tracking and positioning, and quality assurance.

For example, in a quality assurance use case the application on the micro-edge analyzes real-time sensor data and video feeds coming from the connected machine. Depending on the deviation level, either an immediate action can be triggered directly by the micro-edge or the MXIE peer application takes over the monitoring for deeper analysis of real time data for later corrective action. This results in improved latency and optimized network load.

Worker safety remains a high priority for every industrial business, as evidenced by the National Safety Council reporting 2.8 million U.S. non-fatal workplace incidents from 2021 to 2022.This necessitates continuous improvement, including the evaluation and adoption of technology that enhance situational awareness.

The ability to integrate and utilize connected worker data and situational sensory information within MX Grid brings new capabilities for worker safety use cases. For example, the Visual Position and Object Detection (VPOD) application utilizes the MX Grid architecture to process video data next to the camera, together with MXIE, for more accurate asset tracking and positioning. This significantly improves worker safety and contextual awareness, when combined with other OT data sources.

Anna Ahrens, Principal Research Analyst, Manufacturing Technology at OMDIA, said: “We are observing a significant trend of decentralized processing in industrial technology moving compute and AI/ML capabilities to devices near the OT data source. In the upcoming years, we anticipate a steady increase in these connected edge nodes that are the true enablers of the industrial digitalization. Nokia MX Grid addresses these industry needs introducing a transformative decentralized AI/ML processing platform harnessing the power of private wireless connectivity and on-prem OT edge. This innovation facilitates emerging use case scenarios with low latency requirements.”

Stephan Litjens, Vice President of Enterprise Campus Edge Solutions at Nokia, said:
“Achieving Industry 4.0 objectives for enterprises requires effective, responsive, and agile OT decision making based on instant and actionable insights. As part of the Nokia one platform for industrial digitalization, MX Grid enables organizations to harness the power of distributed intelligence by processing and analyzing data closest to the source, resulting in even lower latency and improved responsiveness. This is imperative to achieving priorities such as worker safety, with the new architecture supporting a wide range of mission- and life-critical industrial use cases like predictive maintenance, security and surveillance, and quality assurance.”