Applications of AIS data analysis in bunkering Industry and its related factors

Authors

  • Sumeet Gupta Dr. Sumeet Gupta Associate Professor Head- Center for Infrastructure & Project Finance, Research and Development Centre College of Management and Economic Studies UNIVERSITY OF PETROLEUM & ENERGY STUDIES Energy Acres ,P.O Bidholi Via - Prem Nagar Dehradun -248007 (Uttarakhand) Ph: 0135- 2776091,2776093,2776095, 2102690, 91, 2694257, 201, 203 Extn: 201, Fax : 0135 - 2694204 Mobile : +91 7895617071,9536220716,9319899684 Email : sumeetgupta@ddn.upes.ac.in, sumeetbgh2007@gmail.com
  • Anant Ashish Singh Gupta

DOI:

https://doi.org/10.1956/jge.v18i2.646

Keywords:

AIS, Bunkering Industry

Abstract

In the ocean fuel transportation industry, the optimization of bunkering operations depends on price, position, delays from the expected route, and the cost of delays caused by the bunker operations themselves. Despite their potential importance, detailed bunker activity statistics at each port of call (e.g: waiting time, barge capacity, berth, or berth) are not available. A greater hid deviation from the usual method is that the provider, therefore, arrives past due for a bunker mission. The purchaser commonly has a time slot wherein it anchors as much as acquire bunker. If the bunker barge arrives past due, the purchaser can be beneath neath time strain because of closing dates for shipment, which may also reason the purchaser to interrupt the bunker operation earlier than the agreed quantity of bunker is supplied. This is obtainable confined interest from transport businesses and charterers because the fraudulent quantity is thought to be negligible. However, studies have recommended that the aggregated quantity of misplaced bunker is of big value. To screen such conduct we intend to make use of Automatic Identification System (AIS) statistics from bunker barges and numerous vessels they supply.

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Published

12.06.2022

How to Cite

Gupta, S. and Gupta, A. A. S. (2022) “Applications of AIS data analysis in bunkering Industry and its related factors”, Journal of Global Economy, 18(2), pp. 89–109. doi: 10.1956/jge.v18i2.646.

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