260915 KOMSA AI어선안전설계데이터플랫폼 1화 진수식 송출용

Main Ideas / Concepts

• Fishing vessel accidents are concentrated in small boats (<10 tons) in South Korea

  • 58% of registered vessels are fishing boats.
  • 85% of fishing boats are small (under 10 tons).
  • 66% of all ship accidents occur on fishing vessels—especially on small vessels.
  • Reported figures include:
    • Fishing vessel accidents are 8% of 3,513 total marine accidents.
    • Small fishing vessels under 10 tons account for 53% of all accidents.

• Why accidents happen (especially for small vessels)

  • Captains often handle navigation while working/traveling, increasing collision risk due to:
    • High speed
    • Poor situational awareness
  • Small boats can lose stability and vital functions during net hauling, and sudden waves can trigger capsizing.

• The core problem: not only lack of technology, but lack of data-based safety verification

  • Design culture often treats:
    • Experience as the standard
    • Conventional drawings as the blueprint
  • There is often no standardized, numerical proof step for safety (e.g., stability) during design.
  • Many design firms/shipyards do not accumulate or share data, preventing objective verification.
  • Relying only on regulation/inspection changes is seen as insufficient to shift industry practice.

• Need for a new method/ecosystem

  • A system is needed that:
    • Blocks risks from the design stage
    • Is easy for non-experts to use
    • Supports safe and efficient vessel design at reasonable cost
    • Reflects real field demands

• Solution introduced: an AI-based fishing vessel design data platform (KOMSA / “KIVE/Kive/Chive” as named in subtitles)

  • Built as a web service to support small design studios with limited staff and software resources.
  • Enables design offices/shipyards to:
    • Use an AI-based system to design recommended vessels
    • Receive 3D models, performance & safety data, and basic drawings
    • Manage module data and use related datasets
  • Focuses on “innovation at the design stage” rather than relying primarily on later regulation.

• Ecosystem / virtuous cycle of data and validation

  • The platform improves over time by collecting:
    • Verified standards from designers
    • Personalized designs from fishermen
    • Field data from researchers
  • Claimed outcome:
    • Moves the industry toward safer, more economical ships
    • Enables structurally safer operation beginning from the construction stage
  • Also supports “stable management” by digitizing safety-related data that previously wasn’t managed.

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Methodology / Process Implied

• Problem framing

  • Establish that small fishing vessels dominate accident statistics.
  • Attribute repeat accidents to the absence of data-driven safety verification during design.
  • Note that current practice relies on experience and precedent, not numerical proof.

• Platform approach

  • Build a web-based AI platform for fishing vessel design.
  • Primary users include fishermen, shipowners, and design offices (including small studios).
  • Provide expert-like outputs without requiring specialized personnel by:
    • Reducing reliance on expensive specialized tools/staff via AI-assisted workflows.

• Core platform functions

  • Generate AI-based design plans based on data proven for:
    • Stability / storability (as phrased)
    • Structural safety
  • Output materials for recommended designs:
    • 3D models
    • Performance information
    • Safety data
    • Basic drawings
  • Support engineering data workflows:
    • Module data management
    • Integration/use of related datasets

• Ecosystem validation loop (“virtuous cycle”)

  • Designers contribute verified standards back into the system.
  • Fishermen contribute personalized design needs back into the system.
  • Researchers contribute field data back into the system.
  • The platform refines and expands the standards available to users based on these inputs.

• Expected safety / operational outcomes

  • Reduce risks earlier by performing design-stage evaluation.
  • Help fishermen operate structurally safer boats starting at construction.

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Speakers / Sources Featured

• Unidentified speaker(s)
  • At least one testimonial voice (e.g., statements like “I was half-doubting… after using it…”), including mentions of:
    • Time saved
    • Being a first step toward safety management

• No clearly named individuals

  • Subtitles do not provide specific person names.

• Sources mentioned by organization/type

  • KOMSA / KIVE (AI platform and ecosystem) — the project/platform being described.