One of the significant challenges facing today’s societies is transportation. Moving from one place to another is essential, an unavoidable reality of the life patterns of the contemporary world. Still, it is increasingly essential that this mobility be sustainable and respectful of the environment.
The statistics of the European Union indicate that transport remains one of the primary sources of ‘environmental pressures,’ so it is essential to encourage the use of public transport. When commuting is shared, associated emissions are reduced. This has given new impetus to traveling by train, as it is less polluting than other means. In addition, if specific means of transport are chosen over others, it is also possible to increase the sustainability of the movements of people and goods.
The challenge is not only in understanding how mobility patterns should change but also in convincing citizens to opt for these means of transport compared to alternatives that they consider more comfortable but are less green.
If public transport really and effectively wants to convince consumers, it must prove that it is comfortable, easy to use and, above all, reliable. Citizens want to be sure that they will arrive at the destination at the expected time and that their connections with other means of transport will be as planned.
That is where technology plays a fundamental role and where machine learning and artificial intelligence tools will work as a guarantee to meet expectations.
Passengers have certain expectations when facing a train trip. They want to know when they are going to leave and arrive, that those predictions are fulfilled and that if there are alterations during the journey, they give them detailed and precise information at the exact moment in which things are happening. Artificial intelligence and machine learning are crucial to fulfilling those perspectives. As the whitepaper Prediction Machine: Leverage AI in the Transportation Industry to Make Accurate Predictions explains, technology will be the key to solving transportation challenges.
Big data works as the basis for artificial intelligence and machine learning to work their magic and improve the service offered by transportation companies. Intelligent transport is one of the foundations of smart cities, but benefits and applications go far beyond geographically in the immediate future. All mobility must be smart.
In the case of train travel, machine learning makes it possible to make exact predictions of what the journeys will be like.
The tool allows real-time analysis, calculating what is going to happen and what is happening with much greater precision. In addition, it opens your hand to take into account much more data in analytics. Not only does it matter at what exact time a train leaves a station, but secondary data sources, such as weather information, that impact the journey can also be incorporated into the analysis.
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