A modelling framework of drone deployment for monitoring air pollution from ships
Paper i proceeding, 2019

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.


Jingxu Chen

Hong Kong Polytechnic University

Southeast University

Shuaian Wang

Hong Kong Polytechnic University

Xiaobo Qu

Chalmers, Arkitektur och samhällsbyggnadsteknik, Geologi och geoteknik

Wen Yi

Massey University

Smart Innovation, Systems and Technologies

2190-3018 (ISSN) 2190-3026 (eISSN)

Vol. 98 281-288
978-3-319-92230-0 (ISBN)

11th International KES Conference on Intelligent Interactive Multimedia: Systems and Services, KES-IIMSS 2018
Gold Coast, Australia,


Annan data- och informationsvetenskap

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