Artificial Intelligence Applications for Human-Factor Risk Reduction in Merchant Ship Operations: Regulatory Challenges and Future Maritime Safety Frameworks

UDC.coleccionInvestigación
UDC.departamentoEnxeñaría Industrial
UDC.departamentoCiencias da Navegación e Enxeñaría Mariña
UDC.grupoInvCiencia e Técnica Cibernética (CTC)
UDC.grupoInvGrupo de Enxeñaría Mixto (GEM)
UDC.issue18
UDC.journalTitleElectronics
UDC.startPage4093
UDC.volume15
dc.contributor.authorVázquez Neira, Manuel
dc.contributor.authorPérez Castelo, Francisco Javier
dc.contributor.authorCao-Feijóo, Genaro
dc.contributor.authorOrosa, José A.
dc.date.accessioned2026-10-09T07:38:15Z
dc.date.available2026-10-09T07:38:15Z
dc.date.issued2026-09-10
dc.description.abstract[Abstract] This systematic review examines how artificial intelligence (AI) technologies relevant to human-factor risk reduction can be integrated into international and Spanish maritime safety frameworks. The formal PRISMA corpus comprises 23 core sources (13 peer-reviewed studies and 10 regulatory, institutional or technical documents), while a separate supplementary search provides recent independent technical and regulatory evidence up to 31 August 2026. The analysis covers computer vision, thermal and near-infrared sensing, multimodal fusion, behavioral and fatigue analysis, and onboard edge processing, with particular attention to precision, recall, false alarms, latency, computational requirements and operational robustness. The evidence shows that high detection performance can be achieved in specific maritime datasets, but the reported values depend strongly on the task, sensor, dataset and hardware and cannot be treated as a universal accuracy threshold. A system architecture is therefore proposed in which heterogeneous sensors feed synchronized edge processing, event verification, alarm management, VDR-compatible event logging, and human confirmation with defined fail-safe behavior. On the regulatory side, the study proposes staged adaptations of SOLAS, the ISM Code, STCW, MLC and Spanish inspection frameworks. The 2026 IMO MASS Code, considered as supplementary regulatory evidence, provides a relevant precedent for goal-based approval, risk assessment and progressive operational experience. Fixed tonnage and implementation-date thresholds are consequently treated as illustrative parameters rather than validated requirements; any mandatory carriage provision should be supported by formal safety assessment, type approval and operational evidence. The resulting framework links electronics implementation with a short-, medium- and long-term regulatory roadmap for safer merchant-ship operations.
dc.identifier.citationVázquez Neira, M.; Pérez-Castelo, F.J.; Feijóo, G.C.; Orosa, J.A. Artificial Intelligence Applications for Human-Factor Risk Reduction in Merchant Ship Operations: Regulatory Challenges and Future Maritime Safety Frameworks. Electronics 2026, 15, 4093. https://doi.org/10.3390/electronics15184093
dc.identifier.doi10.3390/electronics15184093
dc.identifier.issn2079-9292
dc.identifier.urihttps://hdl.handle.net/2183/49659
dc.language.isoeng
dc.publisherMDPI
dc.relation.urihttps://doi.org/10.3390/electronics15184093
dc.rightsAttribution 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectArtificial intelligence
dc.subjectMaritime safety
dc.subjectSOLAS
dc.subjectComputer vision
dc.subjectHuman factor
dc.subjectISM code
dc.subjectAutonomous ships
dc.subjectRegulatory framework
dc.subjectMarine accident prevention
dc.subjectShip surveillance
dc.titleArtificial Intelligence Applications for Human-Factor Risk Reduction in Merchant Ship Operations: Regulatory Challenges and Future Maritime Safety Frameworks
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublication4a4b4493-8f36-41dc-a63a-2c69d223da8c
relation.isAuthorOfPublication237ae6e2-af1d-43ba-a1d9-84da5073443b
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relation.isAuthorOfPublication.latestForDiscovery4a4b4493-8f36-41dc-a63a-2c69d223da8c

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