<![CDATA[Indonesia’s inter-island transport network motivates scalable and interoperable maritime information systems. This study develops a four-layer Internet of Things (IoT) and predictive-analytics architecture for port and vessel monitoring and synthesizes relevant peer-reviewed literature with official Indonesian sea-transport publication metadata for 2020–2024. The framework links field sensing (RFID, GNSS and environmental/engine telemetry), multi-protocol communications, edge analytics and port decision-support applications. The original draft reports cargo, ship-call and passenger series; these manuscript-supplied numerical observations are reproduced for editorial traceability but are not independently confirmed against the individual tables in the BPS source PDFs. Consequently, they are treated as figures requiring verification rather than validated empirical findings. The literature supports the technical relevance of IoT-enabled visibility and AIS-based vessel arrival forecasting, but the proposed Indonesian architecture has not been implemented or subjected to operational performance tests. The paper specifies testable performance indicators, data provenance requirements and a deployment pathway for future pilot validation. The principal contribution is therefore a source-traceable conceptual design and an explicit separation between reported statistical observations and untested technological benefits]]>
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