ENBIS-16 in Sheffield

11 – 15 September 2016; Sheffield Abstract submission: 20 March – 4 July 2016

Big Data in the Shipping Industry

13 September 2016, 09:40 – 10:00

Abstract

Submitted by
Ibna Zaman
Authors
Ibna Zaman (Newcastle University), Shirley Coleman (Newcastle University), Kayvan Pazouki (Newcastle University), Rose Norman (Newcastle University)
Abstract
Shipping is one of the oldest industries in the world and the backbone of global commercial trade. The industry nowadays faces challenges due to the current economic situation, new regulations, and lack of innovation. Automation and sensor technology are creating a huge amount of data. By 2020, the annual data generation will be accelerated up to 4300%. Big data has become a buzzword in the industry. It is produced in large volumes in the shipping industry from multiple sources including power systems, engine sensors, navigation and meteorological input. Analysing this big data provides real-time transparency, predictive analysis of the performance and support in decision making. This analysis identifies correlations of different measurable or unmeasurable parameters, discovers hidden patterns and trends. Those analyses will create a great impact in vessel performance monitoring. This paper presents “Auto-Mode Detection” and “ECO Speed” which are data-oriented systems for marine services. Auto Mode Detection system detects the vessel’s mode automatically based on the operational activities. It removes human intervention from the system and helps to monitor the vessel performance based on different operational activities. “ECO Speed” informs the optimum speed of the vessel, estimated fuel consumption and duration for the voyage distance. So the operators can make a decision on the vessel speed for the upcoming journey. Both systems demonstrate how the shipping data is being turned into value. In this way operational data is extending its usefulness into giving real help to management decision making and planning.
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