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Container throughput estimation leveraging ship GPS traces and open data

  • Longbiao Chen
  • , Daqing Zhang
  • , Gang Pan
  • , Leye Wang
  • , Xiaojuan Ma
  • , Chao Chen
  • , Shijian Li
  • Department of Computer Science
  • Zhejiang University
  • Cyber Innovation Joint Research Center
  • Telecom Sudparis
  • Huawei Noah's Ark Lab

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

Traditionally, the port container throughput, a crucial measurement of regional economic development, was manually collected by port authorities. This requires a large amount of human effort and often delays publication of this important figure. In this paper, by leveraging ubiquitous positioning techniques and open data, we propose a twophase approach to estimation of port container throughput in real-time. First, we obtain the number of container ships arriving at berth by analyzing the ships' GPS traces. Then we estimate the throughput of each ship, in terms of number of containers transshipped, by considering the ship's berthing time, capacity, length, breadth, and crane operation performance, as extracted from different data sources. Evaluation results using real-world datasets from Hong Kong and Singapore show that the proposed approach not only estimates the container throughput quite accurately, but also outperforms the baseline method significantly.

Original languageEnglish
Title of host publicationUbiComp 2014 - Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PublisherAssociation for Computing Machinery, Inc
Pages847-851
Number of pages5
ISBN (Electronic)9781450329682
DOIs
Publication statusPublished - 1 Jan 2014
Event2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014 - Seattle, United States
Duration: 13 Sept 201417 Sept 2014

Publication series

NameUbiComp 2014 - Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Conference

Conference2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014
Country/TerritoryUnited States
CitySeattle
Period13/09/1417/09/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Keywords

  • Ais trace
  • Container throughput estimation
  • Open data

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