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All Journal NEUTRON : Research from all areas of the Civil Engineering
Aji Ilham Atthoriq
Narotama University
Civil Engineering, Building, Construction & Architecture Engineering Transportation

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INTERNET OF THINGS (IoT) ARCHITECTURE AND PREDICTIVE ANALYTICS FOR SMART MARITIME TRANSPORTATION: A CONCEPTUAL FRAMEWORK INFORMED BY INDONESIAN PORT STATISTICS Aji Ilham Atthoriq; Sri Wiwoho Mudjanarko; Zailani Abdullah
Neutron Vol 24 No 01 (2024): JULY 2024
Publisher : NAROTAMA UNIVERSITY, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/neutron.v24i01.295

Abstract

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
SMART IoT CONTAINER TRACKING AND PREDICTIVE LOGISTICS FOR ARCHIPELAGIC MARITIME TRANSPORTATION: AN EVIDENCE-BASED SYSTEM DESIGN FOR INDONESIA Aji Ilham Atthoriq; Sapto Budy Wasono; Sajjad Ali Mangi
Neutron Vol 24 No 02 (2025): JANUARY 2025
Publisher : NAROTAMA UNIVERSITY, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/neutron.v24i02.305

Abstract

Tracking containers over archipelagic sea routes requires reliable condition sensing, low-power communication, and interoperability between ships and ports. This paper revises a proposed four-layer Smart Internet of Things (IoT) container tracking architecture for Indonesian maritime logistics using traceable peer-reviewed research, official Statistics Indonesia (BPS) publication records, and International Maritime Organization (IMO) digital reporting requirements. The architecture integrates container sensors, hybrid terrestrial/satellite connectivity, edge-based anomaly detection, and a logistics application interface. We formulate a dimensionally consistent battery-energy model and propose measurable field-validation protocols for telemetry delivery, cold-chain excursion detection, port dwell time, and system reliability. Existing studies support the technical relevance of multi-radio devices and satellite-linked container networks; however, the source manuscript provides no authenticated vessel telemetry, intervention logs, or port-level before-and-after datasets. Consequently, previously stated savings and performance percentages are not reported as empirical findings. This work contributes an auditable engineering design and evaluation framework rather than an unverified effectiveness claim.
Co-Authors Sajjad Ali Mangi Sapto Budy Wasono Sri Wiwoho Mudjanarko, Sri Wiwoho Zailani Abdullah