Why ePIcenter? - Shandong University

The Arctic amplification of global warming is accelerating Arctic maritime transportation. Since 2013, China has sent multiple vessels through Arctic routes every year. In 2017, China incorporated trans-Arctic maritime transportation (i.e. so-called “Silk Route on Ice”) into “the Belt and Road Initiative” with the aim to boost trade between China and Europe. The ePIcenter project is exploring opportunities provided by AI, digitalisation, automation and innovations to enable resilient, efficient and greener supply chains to link with “the Belt and Road Initiative” of China.

Distinguished Professor Zhihua Zhang's Research Group at Shandong University

Distinguished Prof. Zhihua Zhang established the big data mining for climate change research group and the climate modelling laboratory at Shandong University in 2018. With the support of high-resolution climate modelling on blade server groups, the research group is developing a multi-source/multi-dimensional Arctic big data analysis platform for the optimization of Arctic routes.

Management of environmental streaming data to optimize Arctic shipping routes

As a partner of ePIcenter, the Shangdong University research group is focusing on Arctic & New Trade Routes Challenges by using big data and AI technologies, creating powerful solutions to enable resilient, efficient and greener Arctic routes. In this field, Prof. Zhang proposed the near real-time dynamic optimal trans-Arctic route (DOTAR) system, which is the first big data driven Arctic route system internationally (Zhang, 2019). Recently, by making full use of streaming data features, Prof. Zhang used a long short-term memory network with ship/shore-based measurement as training datasets to develop a high-accuracy and continuous Arctic sea ice mapping algorithm, and then optimized Arctic routes in the near real-time manner (Zhang, 2021). Prof Zhang’s management system for trans-Arctic maritime transportation is shown in Figure 1.

Figure 1: Management of environmental steaming data to optimize Arctic routes (Zhang)
Figure 1: Management of environmental steaming data to optimize Arctic routes (Zhang)

Further Reading

  1. Zhihua Zhang, D. Huisingh, M. Song, Exploitation of Trans-Arctic Maritime Transportation, Journal of Cleaner Production, 212, 960-973, 2019.
  2. Zhihua Zhang, M.J.C. Crabbe, Management of Environmental Streaming Data to Optimize Arctic Shipping Routes, Arabian Journal of Geosciences,14, Article number 1441, 2021.