**5. Conclusions**

Oil flow assessment through the MOCs can help increase the security and stability of energy transportation and also enable the discovery of anomalies. To generate statistics on oil flow through MOCs, a maritime oil flow analysis technical framework is proposed. Using the AIS data from 1 January 2014 to 31 December 2016, the framework was applied to four MOCs within the MSR and its surrounding regions. The oil flows through the four chokepoints across four timescales (daily, monthly, seasonal, and annual) were determined and analyzed. The following conclusions were drawn from this study:


By analyzing the above data, we discovered certain patterns as well as anomalies. These discoveries can provide support for national energy transportation strategy formulation, and the prevention and control of abnormalities. However, immense potential exists that can still be mined to provide significant value. Furthermore, with the support of real-time data, the real-time oil flow through the MOCs can be determined. This would be valuable regarding the detection of anomalies in time to aid national emergency responses, among other uses. The framework is suitable for ships carrying only one type of cargo in all MOCs in the world. However, it still has shortcomings, such as not using new technology. In our future research, we will introduce a new time series method to mine deeper information. We will also consider additional variables such as the nationality of the ship and the ship size to expand the breadth of the analysis.

**Author Contributions:** Conceptualization, Yijia Xiao, Yanming Chen, and Manchun Li; Data curation, Yijia Xiao and Zhaojin Yan; Formal analysis, Xiaoqiang Liu, Zhaojin Yan and; Funding acquisition, Yanming Chen, Liang Cheng, and Manchun Li; Investigation, Yanming Chen, Liang Cheng, and Manchun Li; Methodology, Yijia Xiao, Xiaoqiang Liu, and Zhaojin Yan; Project administration, Yanming Chen and Manchun Li; Resources, Liang Cheng; Supervision, Yanming Chen and Manchun Li; Visualization, Yijia Xiao and Zhaojin Yan; Writing—original draft, Yijia Xiao, Xiaoqiang Liu, and Zhaojin Yan; Writing—review & editing, Yanming Chen, Liang Cheng and Manchun Li. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the National Key R&D Plan of China (2017YFB0504205), and the Science and Technology Innovation Project of Nanjing for Overseas Scholars.

**Conflicts of Interest:** The authors declare no conflict of interest.
