Wind turbine equipped with fixed condition-monitoring sensors, edge systems and a professional inspection drone, combining visual, thermal and operational data to support multimodal asset intelligence and earlier utility risk detection.
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Multimodal Asset Intelligence

Multimodal asset intelligence combines Physical AI, computer vision, robotics, IoT and Edge AI with authorized utility information and operational workflows. It helps utilities connect asset conditions with timely decisions while maintaining appropriate human oversight.
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Fragmented asset information limits timely decisions across increasingly complex utility infrastructure
WHY THIS MULTIMODAL ASSET INTELLIGENCE CHALLENGE?
Why Utilities need connected asset intelligence

Utilities are shifting from isolated digital initiatives toward operating models where assets, information, people and external ecosystems must work together in near real time. As previously centralized or manual capabilities become distributed and increasingly intelligent, utilities need architectures that place relevant intelligence close to operational decisions without sacrificing interoperability, cyber resilience or human accountability

Key benefits
Turn asset information into better operational outcomes

Multimodal asset intelligence strengthens how utilities interpret physical conditions and coordinate action across complex asset environments.

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Earlier anomaly detection

Improve the ability to identify developing risks sooner and provide teams with better context for timely operational action.

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Reduced inspection effort

Lower dependence on manual inspection and coordination activities across remote, critical and complex utility infrastructure.

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Improved asset availability

Support more consistent monitoring and maintenance decisions that contribute to reliable asset performance and operational continuity.

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More consistent decisions

Bring relevant operational information into workflows so teams can respond with greater context and reduce fragmented decision-making.

How NTT DATA helps

01
Unify operational information

Connect authorized asset, operational and enterprise information sources required to create a richer view of utility conditions.

Autonomous inspection robot, fixed sensors, edge computing and thermal monitoring systems converging around a critical utility asset to combine multiple data sources into a unified view of equipment condition and operational risk.
02
Contextualize asset data

Organize information around assets and processes so analytics and intelligence can interpret conditions within relevant operational context.

Utility field engineer using a rugged laptop beside remote water infrastructure and connected sensors, applying edge intelligence directly at the asset to support faster local monitoring, analysis and operational decisions.
03
Apply multimodal intelligence

Combine Physical AI, computer vision, robotics, IoT, Edge AI and digital twins at appropriate points across the architecture.

Utility field technician using rugged diagnostic tools and a connected tablet to bring multimodal asset insights directly into frontline maintenance workflows, supporting faster troubleshooting, condition assessment and informed field action.
04
Embed intelligence into operations

Integrate outputs with existing enterprise and operational technology workflows instead of introducing a separate technology layer.

Utility engineers validating secure access, cybersecurity controls and system readiness at industrial automation infrastructure, combining human authorization, operational oversight and fallback safeguards before deploying intelligent technology in critical utility operations.
05
Control progressive deployment

Establish permissions, cyber controls, validation, fallback mechanisms and human oversight, then scale controlled use cases using measurable operational KPIs.

Water treatment facility using a controlled, sensor-enabled pilot process train to measure real operational performance against defined KPIs before expanding multimodal asset intelligence across parallel treatment systems.
Utility maintenance technicians performing condition checks on critical pumping equipment inside a large water infrastructure facility, using digital diagnostics and asset data to identify issues earlier, support proactive maintenance and improve operational reliability.
Proven impact
Multimodal asset intelligence closes the gap between physical conditions, operational context and timely utility action
Results that matter
Performance objectives for connected asset intelligence

Indicative objectives vary according to baseline performance, infrastructure characteristics, process maturity and deployment scope, providing measurable targets for progressively integrated utility operations.

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Shorter operational cycles

Operational cycle time can decrease by 20% to 40%, supporting faster movement from asset information to inspection, assessment and operational action.

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Less manual work

Manual workload can decrease by 20% to 40%, reducing the effort required to inspect assets and coordinate activities across operational environments.

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Faster operational response

Decision and response time can decrease by 15% to 30%, helping teams act sooner when asset conditions or anomalies require attention.

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Greater operational visibility

Significant improvement in operational visibility can give utility teams stronger context across assets, information sources, platforms and frontline operational workflows.

Advance Multimodal Asset Intelligence Across Utility Operations

Work with NTT DATA to connect asset information, distributed intelligence and operational workflows through a controlled, measurable approach to utility modernization.

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