Due to scattered operation, complex operation, intensive labor, open-air operation, man-machine intersection and continuous operation around the clock, there are four characteristics of port operation safety:
Complexity of operation procedure
Variability of operation process
Dynamicity of operation mode
Prone to production accidents
Traditional port business systems are used to build IT infrastructure for operation. As the operation scale is becoming larger and there are more and more equipment types, a large amount of data is generated in operation systems at any time. More than 80% of the data is not utilized effectively. It is called dark data. In recent years, however, more and more ports are developing towards automation and intelligence, and there will be another explosive growth of data. It is urgent to establish a scalable BDA platform, utilize and explore the value of massive data appropriately with it.
Data related to one horizontal (horizontal container circulation process), one vertical (vertical operation management), one chain (logistics service chain) and one network (regional/global port collaboration network) are introduced into the big data platform, and association analysis is carried out from the perspectives of port information BDA and container terminal operations analytics to provide decision-making basis for business improvement.
Powerful data collection, to accept and integrate all machine data;
Efficient data mining to implement multi-dimensional data drilling fast and efficiently;
Fast data analytics, suitable for visualization from front-line workers to decision makers;
Flexible architecture scalability, enabling users to customize functions as needed.
There are many kinds of information management systems. As more and more IT infrastructure are being built, huge data can be generated at any time. Coupled with automation and intelligent transformation in the future, the data volume will grow geometrically. A flexible, scalable set of proven solution and technology is urgent to carry massive data
In the process of long-term information infrastructure construction, the number of systems and suppliers is increasing. However, uniform data standards and specifications are unavailable, resulting in many data islands. It takes much manpower and development time to transform existing systems. The solution must therefore provide full-fledged governance capabilities and extract valuable content from data rapidly while avoiding a lot of investment in development resources;
Multi-dimensional, real-time association analysis of massive data will produce high computational pressure. The technology selected for the scheme must provide sufficient analytics methods when dealing with large-scale data analytics while maximizing the utilization of computing resources.
From the perspective of "one horizontal", information and data throughout horizontal container circulation are integrated and analyzed to help automation systems make optimal decisions.
From the perspective of "one vertical", the original operation mode of traditional TOS for vertical port operations management is transformed, and manual intervention in operations management reduced to provide data analytics basis for decision-making.
From the perspective of "one chain, one network", information flow from and to all participants is improved during the establishment of a sound logistics service chain and regional/global port collaboration network, to enhance service efficiency.