Original scientific paper
https://doi.org/10.31217/p.39.2.8
Developing an AIS Big Data-Driven Framework for Ship Emission Monitoring in Ports
Andi Wibisono
; University of Indonesia, Mechanical Engineering Department, Depok, Jawa Barat, Indonesia
Achmad Riadi
orcid.org/0000-0002-1697-2299
; University of Indonesia, Mechanical Engineering Department, Depok, Jawa Barat, Indonesia
*
Muhammad Taqiyyuddin
; University of Indonesia, Mechanical Engineering Department, Depok, Jawa Barat, Indonesia
Muhammad Budiyanto
; University of Indonesia, Mechanical Engineering Department, Depok, Jawa Barat, Indonesia
Dimas Muzhoffar
; University of Indonesia, Mechanical Engineering Department, Depok, Jawa Barat, Indonesia
* Corresponding author.
Abstract
The rapid expansion of maritime transportation has significantly impacted air quality due to increased ship emissions. This study aims to develop a ship emission monitoring system utilizing Automatic Identification System (AIS) big data, with Tanjung Priok Port in Indonesia (ID TPP) as the case study. The system is designed to monitor and analyze ship emissions based on historical AIS data, providing actionable insights to mitigate environmental impacts. By integrating various data processing techniques, including data preprocessing, database development, sailing time and speed calculation, and emission estimation, this research provides a comprehensive framework for a ship emission monitoring system. The system can be implemented in ports through the development of an interactive web-based dashboard, enhancing the decision-making capabilities of port authorities and other stakeholders. The results demonstrate the system’s potential for effectively monitoring emissions and promoting sustainable maritime operations .
Keywords
Ship emission; Emission monitoring; Tanjung Priok Port; Automatic Identification System (AIS); Big data; Maritime transportation
Hrčak ID:
335898
URI
Publication date:
26.9.2025.
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