Maritime Fleet Management Transformation Using Big Data and IoT
Year: 2025
Type: preprint
Abstract: In today's digital era, maritime fleet management faces major challenges related to port congestion and unpredictable traffic patterns. The main objective of this study is to investigate how the use of big data and the Internet of Things (IoT) can predict maritime traffic patterns and reduce port congestion. [ 1] The methodology used includes analysis of historical data on sea traffic, predictive modeling, and the use of IoT sensors for real-time data collection. Key findings show that the application of this technology can improve the accuracy of traffic predictions by up to 30% and reduce ship waiting times at ports by up to 20%. The conclusion of this study confirms that the integration of big data and IoT can not only optimize fleet management, but also make a significant contribution to port operational efficiency and the overall sustainability of the maritime industry[2][3][4]
Source: SSRN Electronic Journal
DOI: 10.2139/ssrn.5072093
Institution: Politeknik Pelayaran Surabaya
Language: English
Topic: Maritime Ports and Logistics
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4406809506