OPTIMIZING VESSEL ROUTING AND SUSTAINABILITY WITH LAKEHOUSE ARCHITECTURES: A SYSTEMATIC REVIEW - Sudiarsa, I Wayan; Widyantara, I Made Oka; Sudarma, Made; Wirastuti, Ni Made Ary Esta Dewi (Proceeding International Conference on Information Technology, Multimedia, Architecture, Design, and E-Business, 2024)
The growth of maritime transportation underscores the need for advanced data systems to enhance vessel operations. Automatic Identification System (AIS) data generates large volumes of information, requiring efficient architectures for real-time processing and analysis. This systematic literature review examines the use of lakehouse architectures, which combine the flexibility of data lakes with the structured querying of data warehouses, for AIS data integration and analytics. The study highlights how lakehouses improve scalability, data organization, and real-time analysis, enabling practical applications such as anomaly detection, route optimization, and sustainability efforts. Tools like Delta Lake and Apache Hudi are identified as effective solutions, though gaps remain in maritime-specific implementations. This review offers actionable insights and future directions for leveraging lakehouses in maritime data management.