Container and cargo operations at a modern maritime port.
ビジネストーク

海事運用向けAI

Apply computer vision, predictive maintenance and optimization to turn maritime data into earlier, more confident operational decisions.
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Maritime intelligence starts with connected, trusted operational data
なぜ、海運業務にAIが必要なのか？
An AI model cannot compensate for disconnected systems, inconsistent definitions or unclear ownership. Ports and terminals need an authorized data layer that connects relevant operational and enterprise information, preserves context and applies the controls required for dependable use.

With that foundation in place, computer vision can support monitoring, predictive models can identify emerging asset conditions and optimization can help teams prepare operational choices. People remain accountable for decisions that affect safety, security, service continuity and performance.

主なメリット
Turn maritime signals into practical intelligence for safer, more reliable port and terminal operations.
チェックアイコン
See operational conditions earlier

Combine authorized data and visual signals to identify anomalies and emerging risks sooner.

チェックアイコン
Protect asset availability

Use condition and maintenance information to support earlier intervention and better planning.

チェックアイコン
Improve operational coordination

Give teams a more consistent view of activity, constraints and priorities across the terminal.

チェックアイコン
Scale AI with control

Apply data quality, access, monitoring and human-validation rules from pilot through production.

NTTデータのサポート体制は？

01
Prioritize maritime decisions

Assess operational pain points, data readiness and value potential to select use cases with a clear owner, baseline and success measure.

Container ship sailing across the ocean at sunset.
02
Create a trusted operational data layer

Connect the authorized equipment, maintenance, visual and enterprise information required for each use case, with shared definitions, quality controls, security and traceability.

Illustration of AI applications in maritime navigation, logistics and predictive maintenance.
03
Turn visual data into operational awareness

Apply computer vision and video analytics to defined monitoring scenarios, with thresholds, review workflows and human validation appropriate to the operational context.

Port operations team monitoring vessel traffic from a maritime control center.
04
Anticipate asset and operational conditions

Use predictive analytics and optimization to identify emerging patterns, support maintenance planning and prepare better-informed operational choices.

Digital operations specialist monitoring secure data systems and digital identity workflows, supporting blockchain-enabled verification, transparency, provenance and trusted information exchange.
05
Govern, monitor and improve

Track data quality, model behavior, operational outcomes and adoption so the capability can be refined and extended with control.

Personal office reviewing a big screen with a dashboard.
Large container ship sailing across open water at sunset.
実証済みの効果
Measure the operational workflow, not the AI model

AI creates value when it changes the performance of a real maritime workflow. Establish the baseline before implementation and agree the target range, measurement period and accountable data owner for each selected use case.

重要な結果
Connect maritime priorities, trusted data and operating workflows so each AI initiative starts with a defined decision, accountable owner and measurable outcome.
チェックアイコン
Detection and response time

Faster identification, review and response for the selected event type.

チェックアイコン
計画外のダウンタイム

Lower disruption for the equipment and maintenance scope included in the use case.

チェックアイコン
保守計画

Improvement against the approved maintenance baseline or forecast measure.

チェックアイコン
Operational cycle time

Faster coordination or flow for the selected terminal process.

Move from fragmented maritime data to governed operational intelligence

Connect priority use cases, trusted data and port and terminal workflows in a practical roadmap for AI at scale, with measurable outcomes and human oversight built in from the start.

話しましょう

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