Artificial intelligence: Ports are beginning to take up positions
Artificial intelligence (AI) is an affordable technology, although it is only slowly being introduced into the business sector. Thus far, it has primarily been used to improve sales prediction techniques, but its potential applications are infinite and include lowering maintenance costs, improving product quality, planning manufacturing and increasing service level. In the sphere of transport, AI opens up a host of possibilities. Will the ports take advantage of them?
Today, the ports of Hamburg, Rotterdam and Singapore have already started to develop AI tools to improve predictions of maritime and land transport operations. Specifically, Hamburg has created a decision-making support system based on a predictive model of the behaviour of land transport. The model takes historical data, and using deep learning techniques and neural networks, it offers detailed predictions of the times when lorries should reach terminals. Based on this, the system notifies the lorry drivers of the terminal entrance times, and it gives the terminals a dynamic forecast of the workload they will have according to the changes in the surrounding conditions (road and access route saturation, real ship arrival time, degree of terminal saturation, etc.).
HOW DOES DEEP LEARNING WORK?
Deep learning and neural networks are two of the machine-learning methods which have come to the fore the most in recent years. They are inspired by the way neural networks work in the brain. They transform the entry values, layer by layer, until the value of the variables that they are trying to predict is found. Even though the results of neural networks are quite satisfactory, they need vast amounts of data to learn, and learning times are long (days or even weeks). Natural language processing, image pattern recognition and voice processing are the main success stories of deep learning. Thus, the evolution of data collection and management has to include the following levels: recording, analysing, simulating, predicting and finally recommending. Based on that, new-generation ports are expected to apply predictive and prescriptive analysis techniques as tools to support decision-making when planning the transport of the actors in the port-logistics chain. And this does not only include lorries, since the same transport logistics that it applied on motorways can also be applied to any means of transport (railway, maritime or river).
Ports that already have advanced systems that allow them to gather a significant amount of data will be the best poised to successfully incorporate the tools offered by artificial intelligence
THE ORIGINS OF ARTIFICIAL INTELLIGENCE
Even though it seems like a recent concept, the origins of artificial intelligence date back to the Greeks. Aristotle (384-322 BC) was the first to determine a set of rules that partly describes the way the mind works to reach rational conclusions, and Ctesibius of Alexandria (285-222 BC) built the first self-controlled machine, a water-flow regulator (rational, but without the ability to reason). John McCarthy, Marvin Minsky and Claude Shannon coined the term artificial intelligence at the Dartmouth Workshop (USA) in 1956 to refer to the “science and inventiveness of making intelligent machines, especially intelligent calculation programmes”. Where these three scientists missed the mark was in their prediction of when the first smart machines would arrive. They trusted that by the 1970s we would be surrounded by artificial intelligence. However, the majority of tech companies did not decide to make significant investments in this field until the 1990s and 2000s, in a bid to improve the processing and analytical capacity of the vast amounts of data which were being generated in the new digital world. In fact, AI was definitively enshrined in 1997, when IBM demonstrated that an IT system was capable of beating a human at chess. And it wasn’t just any human; it was the world champion, Garry Kasparov. The supercomputer was called Deep Blue, and it marked the turning point when industrial technology and society at large became aware of the real importance and possibilities of artificial intelligence.