{
  "id": "AIBD-0250",
  "title": "Fujitsu Zinrai collision-risk prediction trialled with the Japan Coast Guard at the Tokyo Wan Vessel Traffic Service Center: warnings about two minutes earlier, nearly double the warnings",
  "summary": "The Maritime Executive (15 Apr 2020): in a Dec 2019 to Mar 2020 trial, six experienced controllers re-ran past near-miss cases with and without AI risk predictions from AIS and radar data; warnings...",
  "date_observed": "2020-04-15",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "The Maritime Executive reported on 15 Apr 2020 that Fujitsu Limited and the Japan Coast Guard had field-tested an artificial-intelligence system to predict vessel collisions. The test ran from December 2019 to March 2020 at the Tokyo Wan Vessel Traffic Service Center. It provides navigation support under an outsourcing contract with the Coast Guard. It uses Fujitsu Human Centric AI Zinrai from Fujitsu Laboratories. The technology detects near misses between vessels and predicts areas where collision risk concentrates in Tokyo Bay. In the center's training environment, six experienced maritime traffic controllers and instructors simulated control tasks based on past near-miss accidents. They compared conventional operation with operation supported by risk information computed from past AIS data and Coast Guard risk-recommendation records. It shortened the time before a controller sent a risk warning to a vessel by an average of about two minutes. The number of warnings issued to risk-prone vessels nearly doubled, and it was found particularly effective for newcomers. The article cites the Japan Transport Safety Board's count of 2,863 marine collisions in Japan from 2009 to 2019. The results come from a simulation, not live traffic.",
  "category": "general benefit",
  "unexpected": false,
  "purpose": "The technology was built to detect near misses and predict collision-risk areas to help vessel traffic controllers warn ships earlier.",
  "system": "Fujitsu Human Centric AI Zinrai collision-risk prediction using AIS and radar data",
  "model_version": "Fujitsu Human Centric AI Zinrai",
  "developer": "Fujitsu Laboratories / Fujitsu Limited",
  "deployer": "Japan Coast Guard, Tokyo Wan Vessel Traffic Service Center (trial)",
  "location": null,
  "domain": "Maritime safety",
  "segment": "Vessel traffic services / collision-risk prediction",
  "benefit_type": "Reduced Task Time",
  "taxonomy_note": "The trial was simulated, and the earlier warning serves collision avoidance, which no measured outcome documents.",
  "registry_ids": {},
  "ratings": [
    {
      "group": "organizational",
      "depth": null,
      "reason": "Simulation results only. No live operational outcome is documented."
    },
    {
      "group": "societal",
      "depth": null,
      "reason": "No collision avoided or reduced is documented."
    },
    {
      "group": "personal",
      "depth": null,
      "reason": "No individual outcome is documented."
    }
  ],
  "ai_role": {
    "status": "assessed",
    "statement": "The AI produced risk information that controllers used to decide warnings. The two-minute gain and doubled warning count were measured against conventional operation in replayed near-miss scenarios with six controllers."
  },
  "evidence": [
    {
      "kind": "news report",
      "citation": "The Maritime Executive (15 Apr 2020). AI System Tested by Tokyo Bay Vessel Traffic Controllers.",
      "title": "AI System Tested by Tokyo Bay Vessel Traffic Controllers",
      "url": "https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers",
      "date": "2020-04-15",
      "written_by": "independent",
      "quote": "It was also confirmed that the number of warnings issued for risk-prone vessels nearly doubled with the technology, indicating proactive preventive measures"
    },
    {
      "kind": "registry label",
      "citation": "OECD AI Incidents and Hazards Monitor, incident 2020-04-16-d2f1: Fujitsu AI System Reduces Ship Collision Risks in Tokyo Bay Trial.",
      "title": "Fujitsu AI System Reduces Ship Collision Risks in Tokyo Bay Trial",
      "url": "https://oecd.ai/en/incidents/2020-04-16-d2f1",
      "date": "2020-04-16",
      "written_by": "independent",
      "quote": "Fujitsu, in partnership with the Japan Coast Guard, tested its Zinrai AI system in Tokyo Bay from December 2019 to March 2020."
    },
    {
      "kind": "press release",
      "citation": "Fujitsu Limited (28 Sep 2021). Fujitsu Introduces AI technology Enabling Highly Accurate Prediction of Vessel Collision Risks on Complex Maritime Routes.",
      "title": "Fujitsu Introduces AI technology Enabling Highly Accurate Prediction of Vessel Collision Risks on Complex Maritime Routes",
      "url": "https://info.archives.global.fujitsu/global/about/resources/news/press-releases/2021/0928-01.html",
      "date": "2021-09-28",
      "written_by": "makers",
      "quote": null
    }
  ],
  "replication": {
    "produced_by": [
      "A VTS center with radar and AIS feeds and archived risk recommendations",
      "Replayed near-miss scenarios in a training environment",
      "Experienced controllers comparing conventional and AI-supported operation"
    ],
    "must_hold": [
      "Risk predictions are computed in real time on live traffic",
      "Controllers trust and act on the predictions"
    ],
    "echoes": [
      {
        "date": "2026-04-15",
        "setting": "Shipboard AI watchkeeping (Orca AI) on 139 container ships: 52% fewer high-severity close encounters in the first year, per a NorthStandard study",
        "model_version": null,
        "outcome": "unknown",
        "source": "https://www.rivieramm.com/news-content-hub/news-content-hub/northstandard-study-demonstrates-benefits-of-ai-navigation-support-88473"
      }
    ]
  },
  "paired_incident": null,
  "headline": "Fujitsu Zinrai trial speeds vessel warnings by about two minutes",
  "metric": "the number of warnings issued to risk-prone vessels nearly doubled",
  "comparator": {
    "against": "conventional control operation without AI risk information, in a simulation of past near-miss cases",
    "before": "conventional operation (no absolute figure given)",
    "after": "risk warning sent an average of approximately two minutes earlier; number of warnings issued for risk-prone vessels nearly doubled",
    "basis": "measured",
    "quote": "It was found that the new technology could shorten the time before a risk warning is sent to a vessel by the operation controller by an average of approximately two minutes, enabling the early detection of vessels at risk of collision. It was also confirmed that the number of warnings issued for risk-prone vessels nearly doubled with the technology, indicating proactive preventive measures and the potential to enhance safety in Tokyo Bay.",
    "url": "https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers"
  },
  "later": {
    "status": "persisted",
    "date": "2021-09-28",
    "note": "Fujitsu ran a second field trial at the same center from 17 November 2020 to 2 September 2021 with an added course-following algorithm, reported about 90% fewer unnecessary alerts than the earlier technology, and planned a commercial navigation-support service from March 2022.",
    "quote": "Results of the trial demonstrated that this technology can reduce unnecessary alerts by about 90% on all sea routes, especially on curved sections where alerts frequently occurred.",
    "url": "https://info.archives.global.fujitsu/global/about/resources/news/press-releases/2021/0928-01.html"
  },
  "value": null,
  "developer_country": "Japan",
  "deployer_country": "Japan",
  "unrated_because": null,
  "brief_notes": null,
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  "revisions": [
    {
      "date": "2026-10-20",
      "change": "Record drafted from the cited sources.",
      "source": null,
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.",
      "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.",
      "source": "https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers; https://info.archives.global.fujitsu/global/about/resources/news/press-releases/2021/0928-01.html; https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Country of the developer and the deployer added from the organization's own site or a registry.",
      "source": "https://en.wikipedia.org/wiki/Fujitsu; https://en.wikipedia.org/wiki/Japan_Coast_Guard",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
      "source": null,
      "editor": "AIBD"
    }
  ],
  "confidence": "reported",
  "shade": "medium",
  "claim_status": "Independently reported",
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          "kind": "record_fields",
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            "account": "The Maritime Executive reported on 15 Apr 2020 that Fujitsu Limited and the Japan Coast Guard had field-tested an artificial-intelligence system to predict vessel collisions. The test ran from December 2019 to March 2020 at the Tokyo Wan Vessel Traffic Service Center. It provides navigation support under an outsourcing contract with the Coast Guard. It uses Fujitsu Human Centric AI Zinrai from Fujitsu Laboratories. The technology detects near misses between vessels and predicts areas where collision risk concentrates in Tokyo Bay. In the center's training environment, six experienced maritime traffic controllers and instructors simulated control tasks based on past near-miss accidents. They compared conventional operation with operation supported by risk information computed from past AIS data and Coast Guard risk-recommendation records. It shortened the time before a controller sent a risk warning to a vessel by an average of about two minutes. The number of warnings issued to risk-prone vessels nearly doubled, and it was found particularly effective for newcomers. The article cites the Japan Transport Safety Board's count of 2,863 marine collisions in Japan from 2009 to 2019. The results come from a simulation, not live traffic.",
            "replication": {
              "produced_by": [
                "A VTS center with radar and AIS feeds and archived risk recommendations",
                "Replayed near-miss scenarios in a training environment",
                "Experienced controllers comparing conventional and AI-supported operation"
              ],
              "must_hold": [
                "Risk predictions are computed in real time on live traffic",
                "Controllers trust and act on the predictions"
              ],
              "echoes": [
                {
                  "date": "2026-04-15",
                  "setting": "Shipboard AI watchkeeping (Orca AI) on 139 container ships: 52% fewer high-severity close encounters in the first year, per a NorthStandard study",
                  "outcome": "unknown",
                  "source": "https://www.rivieramm.com/news-content-hub/news-content-hub/northstandard-study-demonstrates-benefits-of-ai-navigation-support-88473"
                }
              ]
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "account",
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      }
    },
    "summary": {
      "total": 91,
      "addressed": 91,
      "known": 31,
      "reviewed": 0,
      "record_mapped": 31,
      "not_assessed": 60,
      "complete": false,
      "by_state": {
        "value_present": 31,
        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 60,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}