Abstract
Cargo ship vessels have been widely used in the global trade market. Disruptions or failure of the cargo ship vessel report can considerably impact the supply chain in global trade. Thus, it is considered to have a timely intervention and monitoring of the ship vessels to get the status of the vessels. This paper discusses the idealogy of the statistical way of analyzing the ship vessel data based on the time difference and the speed over the ground. Monitoring the cargo ships all time is not feasible because of a high number of instances. The proposed approach results in the statistical threshold limits reducing the cases we must pay attention to the surveillance of the cargo ship vessels.
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Radhakrishnan, H.K., Sundar, S., Bharath, R., Ramanarayanan, C.P. (2023). Suspicious Event Detection of Cargo Vessels Based on AIS Data. In: Sharma, N., Goje, A., Chakrabarti, A., Bruckstein, A.M. (eds) Data Management, Analytics and Innovation. ICDMAI 2023. Lecture Notes in Networks and Systems, vol 662. Springer, Singapore. https://doi.org/10.1007/978-981-99-1414-2_8
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DOI: https://doi.org/10.1007/978-981-99-1414-2_8
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