EDGE COMPUTING
Scaling real-time systems A recurring challenge in real-time processing is scaling systems from initial deployments to broader operations. NTT DATA addresses this through repeatable solutions and standardised architectures, particularly within the private 5G and edge AI partnership with Ericsson.
These solutions are designed for deployment across sectors including manufacturing, transport, energy and urban infrastructure. Each environment requires adaptation, but the underlying architecture remains consistent. This supports faster deployment and reduces integration effort.
Scaling also depends on operational governance. Systems must maintain performance across multiple sites while handling variations in data, infrastructure and regulatory requirements. Managed services provide a framework for maintaining this consistency.
The company’ s approach reflects a shift towards operational platforms rather than isolated solutions. Realtime processing becomes part of a wider system that includes connectivity, compute and service management.
Operational control and safety Real-time processing introduces operational considerations related to control and safety. Systems that act on live data must operate within defined parameters to prevent unintended outcomes. NTT DATA incorporates safeguards within its deployments, particularly in environments such as data centres and industrial operations.
“ The expertise of NTT DATA and Ericsson integrates edge AI and physical AI with enhanced connectivity, overcoming operational, scalability and accountability challenges and accelerating the deployment of AI with confidence”
Alejandro Cadenas Associate Vice President, Worldwide Telco Research & Consulting, 5G, IoT and Mobility IDC
In the Rhine-Ruhr 1 project, optimisation actions are restricted if system conditions fall outside defined ranges or if communication issues occur. Operators retain oversight and can intervene when necessary. This ensures that automation does not override operational constraints.
Such controls are essential in environments where system actions have direct physical impact. Realtime processing must balance responsiveness with reliability, ensuring that systems remain predictable under varying conditions.
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