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A Modelling Framework of Drone Deployment for Monitoring Air Pollution from Ships

  • Jingxu Chen
  • Shuaian Wang
  • Xiaobo Qu
  • Wen Yi
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 98)

Abstract

Sulphur oxide (SOx) emissions impose a serious health threat to the residents and a substantial cost to the local environment. In many countries and regions, ocean-going vessels are mandated to use low-sulphur fuel when docking at emission control areas. Recently, drones have been identified as an efficient way to detect non-compliance of ships, as they offer the advantage of covering a wide range of surveillance areas. To date, the managerial perspective of the deployment of a fleet of drones to inspect air pollution from ships has not been addressed yet. In this paper, we propose a modelling framework of drone deployment. It contains three components: drone scheduling at the operational level, drone assignment at the tactical level and drone base station location at the strategic level.

Notes

Acknowledgment

This research is sponsored by Environment and Conservation Fund Project 92/2017 and the Youth Program (No. 71501038), General Project (No. 71771050), Key Projects (No. 51638004) of the National Natural Science Foundation of China, and the Natural Science Foundation of Jiangsu Province in China (BK20150603). The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any agency of government.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Logistics and Maritime StudiesThe Hong Kong Polytechnic UniversityHung Hom, KowloonHong Kong
  2. 2.Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic TechnologiesSoutheast UniversityNanjingChina
  3. 3.Department of Architecture and Civil EngineeringChalmers University of TechnologyGothenburgSweden
  4. 4.School of Engineering and Advanced Technology, College of SciencesMassey UniversityAucklandNew Zealand

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