Improving port productivity may be currently one of the most common and prioritized agendas for international port business community, particularly for the global container terminal operators. This is likely a reflection of recent change in business environment at ports, which have been traditionally essential logistics infrastructures in a global trade and industry networks. There is no doubt that the modern world economy fully depends on the global production network and sophisticated supply chain management. Nowadays, materials, parts and components for automotive assembly lines, for example, are gathered across oceans in a regular basis, hence ports, as essential connecting nodes of waterborne and land transportation networks, are one of key players of global production activities. In this context, extremely sophisticated but complicated modern supply chain management requires more time and cost consciousness to the port community, resulting in introduction of recent cut-edging information and communication technology (ICT) for improving port operation efficiency and productivity. The global port operators are now facing the client’s strong requests to provide more quality logistics services with less port charges.
Recently, a new policy reform, Industry 4.0, were launched by Germany, which aims at introducing automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things (IoT), cloud computing and cognitive computing. An artificial intelligence (AI) based on deep learning programing, accurate sensor technology and big data attracts now a biggest attention of the world business community. In line with this recent trend, port community are going to step in the more ICT based and client oriented port operation and management.
An example may be the smart-PORT logistics (SPL) concept initiated by the port of Hamburg, Germany, which includes IT based traffic management system and real time information on traffic and port infrastructure along with the demand-oriented networking via a central public cloud. While the services have been just started after several years pilot phase, the SPL may be thought to pave the way of dramatically changing the future port operation scene.
Considering to these global trend of creating more smart and competitive ports , the government of Japan decided to launch, as a part of port policy reforms, a new policy, namely “AI port initiatives”, for improving port operation productivity and port traffic traceability through employing AI for port terminal operation system configuration. The new terminal control system is expected to enable AI independently to operate container yard cranes for minimizing crane movements. AI controlled terminal operation system is also expected to manage container dray traffic at port for realizing quick container check-in and delivery.
An advantage of introducing AI into container terminal operation is considered to allow port terminal operators: i) collecting, processing and storing a bulky data without no terminal staff intervention, because the data is generated from daily terminal operation on 24 hours and 365 day per year basis (big data), ii) providing an indicative optimum solution and best practices including best stowage and yard plans with terminal staff for assisting prompt decision making based on the past experiences and big data and iii) quickly controlling and processing container cargo traffic by fully automatizing container yard and gate operations.
Major challenges however may include: i) smooth introduction of the newest sensor technologies for efficiently and effectively collecting all terminal operation related information as digital data, ii) materializing an accurate big data transmission between on-site sensors and the terminal control host computer through IoT, iii) appropriate man-machine interface for assisting operator’s prompt decision making, iv) renovating current terminal operating system by employing AI based architecture, and v) appropriate countermeasures against computer virus and hacking. A variety of deep learning software is currently available including many open software. Mobilizing these existing software resources may save the project time and cost, and enable to input more human and financial resources for developing AI loaded terminal operation system. Most advanced sensor technology such as image processing techniques also may contribute, as eyes of AI, to the system development.
The ICT based management and operation system may provide us with an attractive solution to dramatically increase port efficiency and competitiveness, to contribute to the global logistics innovation, and to improve business profitability and working environment at ports. At the same time, however, we must carefully consider and discuss the best course to invite AI into our ports as a good partner. The port community are not welcome to build a robot port. What needed in a practical viewpoint may be how to create a well-designed human-AI collaborative system for making our port operation and management smart. This may be a common business interest of the global port community and a common challenge, therefore to be discussed accordingly.