Development of an IoT-Based Ship Engine Performance Monitoring System to Enhance Operational Efficiency

This research aims to develop an IoT-based ship engine performance monitoring system to enhance operational efficiency in marine vessels. The study introduces a real-time monitoring prototype integrating sensors, microcontrollers, and cloud-based data visualization. The variables observed include engine temperature, RPM, and fuel consumption. The methodology follows a design and implementation approach, tested on a diesel-powered training ship over a two-week observation period. Data were collected continuously and analyzed to detect performance anomalies and efficiency trends. Results show that the system improves situational awareness and enables proactive maintenance decisions. The developed system has implications for reducing fuel costs, extending engine life, and supporting digital transformation in marine engineering operations

Authors

Institutions

Publication Details

Journal
Formosa Journal of Computer and Information Science
Published
2025-03-26
DOI
https://doi.org/10.55927/fjcis.v4i1.14134
Primary Topic
Marine and Coastal Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of an IoT-Based Ship Engine Performance Monitoring System to Enhance Operational Efficiency

Urip Mudjiono, Endang Pudji Purwanti, Imam Sutrisno, Nafi Almuzani et al.
Formosa Journal of Computer and Information Science
Marine and Coastal Research
article

Development of an IoT-Based Ship Engine Performance Monitoring System to Enhance Operational Efficiency

Urip Mudjiono, Endang Pudji Purwanti, Imam Sutrisno, Nafi Almuzani, Projek Priyonggo, Fahmi Umasangadji, Ardiansyah Ardiansyah, Achmad Bashori
article en

Abstract

This research aims to develop an IoT-based ship engine performance monitoring system to enhance operational efficiency in marine vessels. The study introduces a real-time monitoring prototype integrating sensors, microcontrollers, and cloud-based data visualization. The variables observed include engine temperature, RPM, and fuel consumption. The methodology follows a design and implementation approach, tested on a diesel-powered training ship over a two-week observation period. Data were collected continuously and analyzed to detect performance anomalies and efficiency trends. Results show that the system improves situational awareness and enables proactive maintenance decisions. The developed system has implications for reducing fuel costs, extending engine life, and supporting digital transformation in marine engineering operations

Formosa Journal of Computer and Information ScienceVol. 4(1)
Universitas Patria Artha (ID)
Openalex Percentile: Top 91%
Marine and Coastal Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.