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@article{179212,
        author = {Isaindhiniya M and Subanetha G and Swetha R and Ashwathy A and V Gnanasekar},
        title = {SEVORA: Sea Voice Operation and Reporting Assistant},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7133-7139},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179212},
        abstract = {The maritime industry faces complex communication and documentation challenges due to multilingual crew interactions, extensive paperwork, and manual safety reporting. SEVORA (Sea Voice Operation and Reporting Assistant) is a prototype designed to resolve these issues by combining voice-to-text transcription, multilingual translation, and AI-based reporting systems. Leveraging OpenAI Whisper for real-time transcription, the RAG model for documentation retrieval, and multilingual Text-to-Speech (TTS), SEVORA improves operational efficiency, ensures safety compliance, and enhances communication in maritime settings. The system integrates with ship management databases and uses MongoDB for secure data handling, including both infrastructure and identity-based access (IAM) controls.},
        keywords = {Voice-to-Text, Maritime AI, Multilingual Reporting, RAG Model, Whisper, TTS, Safety Reporting, MongoDB, IAM, AI Automation},
        month = {May},
        }