Technology

Will AI take over port management?

Artificial Intelligence is already being applied in ports. There are several pilot tests and applications that have taken the concept of smart ports further. But to find out what exactly is being done and, above all, what may happen in the future, we have asked the leading expert in the field: AI itself.

Posted on 05.11.2023

PierNext

AI responds on its role in the present and future management of the ports. ( Performed with AI )

The first question we asked is how an AI can help port management

It replied that artificial intelligence (AI) can play a very important role in port management.

In particular:

Real-time maritime traffic management by analysing traffic data and predicting vessel demand in a given port. It can also help optimise the use of port space and improve traffic planning and scheduling.
Optimising loading and unloading by analysing real-time data and identifying bottlenecks and delays in processes. It can also help to schedule and coordinate these operations more efficiently.
Predictive maintenance by analysing data from sensors and monitoring equipment in real time. This can help prevent failures and reduce downtime.
Supply chain management by providing real-time, predictive analysis of loading and unloading demand, which helps reduce delays in processing and storage of goods.
Improving port security by analysing data from sensors and security cameras to detect potential threats and prevent accidents.

We then asked to give us some examples of artificial intelligence currently in operation in ports

It gave us 3 examples:

The Port of Rotterdam is using an artificial intelligence system called "Pronto", which uses sensor data to improve the planning and coordination of container loading and unloading. The Pronto system uses machine learning models to predict the arrival time of ships and the processing time for loading and unloading containers.
The Port of Los Angeles is using an artificial intelligence system called "Port Optimizer", which uses sensor data and predictive analytics to improve the scheduling and coordination of container loading and unloading. The Port Optimizer system uses machine learning algorithms to predict demand and to optimise the scheduling and coordination of port operations.
The Port of Singapore is using an artificial intelligence system called "Maritime Single Window", which uses predictive analytics and natural language processing to improve efficiency and transparency in customs and immigration control processes. The Maritime Single Window system uses machine learning algorithms to analyse and classify data from shipping and customs documents, helping to reduce processing times and improve efficiency in port management.

Once we have some examples of its application, we asked about the first steps ports should take to adapt to artificial intelligence.

The AI responds with 6 points to consider:

Identify areas for improvement, in particular, efficiency and productivity. Automating container management, optimising shipping routes, predicting cargo demand and detecting fraud are some examples of areas where AI could be useful.
Assess data availability. AI depends on large amounts of data to function. Therefore, ports should assess data availability and consider integrating systems to collect additional data if necessary.
Assess infrastructure capacity such as network bandwidth and data storage to determine if they are ready to support the needs of AI systems.
Establish an AI team to lead the implementation of AI projects and ensure proper integration of systems.
Assess the costs and benefits of implementing AI systems and determine whether the investment is worthwhile.
Establish partnerships with specialised AI companies to assist in the implementation of systems and gain additional expertise in the field.

In addition to ports, we asked which shipping companies have implemented artificial intelligence models.

Here, too, it gave us concrete examples of companies and their application:

Maersk started to use artificial intelligence in several areas of its business. For example, it has developed an AI system called "Captain Peter" that uses sensor data and machine learning models to help captains optimise fuel consumption and reduce CO2 emissions.
CMA CGM has developed an artificial intelligence platform called "Smart Containers" that uses sensors and machine learning algorithms to monitor the condition of containers during transport. This allows customers to track in real time the location, temperature, humidity and other parameters of the products transported in the containers.
Hapag-Lloyd has started using artificial intelligence in its maritime route planning system. The system uses weather, shipping traffic and fuel data to optimise ship routes and reduce operating costs.
MSC has developed an artificial intelligence platform called "Safeguard" that uses sensor data and machine learning models to monitor ship safety and prevent accidents. The platform also provides real-time alerts on emergency situations to crew and shore crew.
Evergreen Line has started using artificial intelligence in its predictive maintenance system. The system uses sensors and machine learning algorithms to monitor the condition of equipment on ships and predict when maintenance work is due.

After reviewing the application of AI in ports and shipping, we asked it to come up with future scenarios of its use in 1, 2, 3, 4 and 5 years

It responded that artificial intelligence (AI) is significantly impacting port management and shipping. Its role is expected to continue to grow in the near future, although it notes that the pace and direction of AI advancement in port management and shipping may vary depending on the economic, political and technological factors influencing the industry:

In 1 year:

AI is expected to remain a key tool to improve efficiency and transparency in port management, enabling port operators to better plan and coordinate loading and unloading operations.
In navigation, AI will continue to be used to improve safety and efficiency in route planning, optimisation of fuel consumption and cargo management.

In 2 years:

AI is expected to be increasingly used in the automation of routine and repetitive tasks in port management, allowing port operators to devote more time and resources to higher value tasks.
In navigation, it is expected to be increasingly used in the automation of navigation tasks, such as obstacle detection and route management, which will reduce the manual work of crew members.

In 3 years:

AI is expected to be increasingly used for the detection and prevention of risk situations, such as collisions and accidents in port management and shipping.
In shipping, AI will increasingly be used to improve the efficiency of offshore operations, such as crew management and preventive maintenance of equipment.

In 4 years

AI is expected to be increasingly used for supply chain management in the maritime sector, allowing for greater visibility and transparency in the transport of goods.
In shipping, AI will increasingly be used to improve safety in ports and terminals by detecting potential risks and dangerous situations before they occur.

In 5 years:

It is predicted that AI will increasingly be used for autonomous decision-making in port management and shipping, leading to more efficient and faster operations.
In shipping, AI is expected to be increasingly used in the full automation of ships, enabling autonomous navigation and reducing operational costs.

The next question is unavoidable when talking about AI: to what extent are jobs endangered?

First, it answers positively, stating that the use of artificial intelligence (AI) in ports and the maritime industry in general has the potential to improve efficiency and productivity, reduce costs and improve safety. Then, of course, it goes on to say that it can also have an impact on jobs:

It is important to note that AI will not necessarily replace workers, but may change the nature of jobs and require different skills and knowledge. For example, workers may need skills in data analysis, programming and maintenance of automated systems.

In some cases, AI may automate certain tasks previously performed by human workers, which may reduce the number of employees needed. For example, automating the loading and unloading of containers at ports can reduce the need for manpower.

However, it is also important to note that AI can create new jobs in areas such as the development and maintenance of AI systems, data analysis and programming. In addition, AI can improve workplace safety by reducing the need for dangerous or high-risk jobs.

And it ends:

While AI can have an impact on jobs in the maritime industry, it can also generate new job opportunities and improve workplace safety. It is important that companies and workers are prepared to adapt to the changes and acquire new skills and knowledge to make the most of the benefits of AI in the maritime industry.

We went beyond theory and asked if it really believes it is feasible for a container terminal to be run entirely by an AI

In practice, there are still many challenges to overcome before it becomes a reality.

Managing a container terminal involves many complex tasks that require a combination of human and technological skills. Some of these tasks include planning the loading and unloading of containers, monitoring terminal machinery, managing inventory and coordinating with other ports and shipping companies.

While AI can be very useful for some of these tasks, such as planning and monitoring the loading and unloading of containers, there are still many tasks that require human intervention, especially when dealing with unforeseen situations or technical problems in the machinery.

In addition, managing a container terminal is a highly collaborative process involving many stakeholders, including terminal operators, shippers, importers and exporters. AI can improve efficiency and coordination in this process, but it cannot completely replace human collaboration.

In conclusion, it is unlikely that a container terminal can be fully managed by AI in the short to medium term. It is more likely that AI will be used to complement human skills in terminal management and improve efficiency and coordination in the container handling process.

And while we're at it, we also asked him if the management of all internal and external traffic in a port, trucks, railways, etc. could be automated thanks to an AI

According to our ‘interviewee’, the management of all internal and external traffic in a port, including trucks and railways, "can benefit" from automation with the help of artificial intelligence (AI).

AI can help in optimising logistics and traffic coordination, enabling forecasting and management of high demand or congestion situations. It can also assist in route optimisation and schedule planning, which can improve efficiency and reduce waiting times.

However, it is important to note that full automation of traffic management may not be possible in the short term due to the complexity of the port environment and the need for coordination between different stakeholders. In addition, the technology is not yet fully mature and requires human intervention in case of unforeseen situations.

In conclusion, although AI can significantly improve traffic management in a port, full automation is unlikely to be feasible in the short term. An integrated approach combining technology with human intervention will be necessary to achieve efficient and effective port traffic management.

This is what AI thinks of the application of artificial intelligence in ports and the shipping sector. We shall see what it thinks in 6 months' time.

In any case, it is a clarifying exercise, pointing out possible routes to be followed without a pre-established navigational chart.

Although from this point onwards, as the old maps and charts remind us, it is an unknown land.

Topics

A