The advancement of sensor technology and connectivity is proving to be a turning point for trains. Sensors and big data analytics are helping to maintain trains more efficiently. This is a development that has come into place since 4G technology became available as it allows data to be processed faster. The data that is gathered by sensors includes check-in data, data about tracks and information that is sent by sensors that are in the trains.

In the Netherlands, data helps in keeping things moving and aids in the delivery of safer, easier and better travel for passengers. The data collected plays a critical role in business intelligence. It allows data to be converted into reports that are useful for continuous improvement and management of train transport. With the help of advanced data analytics, passenger experience has improved tremendously. The patterns from data allow the development of new applications that makes booking and travel, in general a much better experience. Moreover, tracking data from stations simplifies the calculation of passenger numbers by weighing the trains. The identification of these numbers helps in finding if there is a likelihood of empty seats or not. Big data analytics is improving creativity and standardization in this sector through informed decision making that is highly appreciated in a competitive environment.

Multiple factors

Through a combination of big data analytics and predictive maintenance, issues associated with overheating and mechanical failure can be addressed with ease and in a timely manner. This is done by fitting multiple sensors in locomotives to provide data on the condition of various parts of the train. It allows parts that show signs of failure to be replaced before they fail and cause delays. With these capabilities, data and real-time analytics are ensuring that trains are always moving at all times and delays are minimized. Freezing that is one of the problems facing trains in the region and is being addressed with the aid of real-time analytics. Predictive maintenance and analytics ease de-icing by helping pinpoint precisely the train and a part that needs de-icing.

Collected data provides greater equipment availability and reduces delay for travellers. These aspects have also made total failure of trains rare while at the same time improving locomotives’ return on investment due to the automated functions. In the event of a crash, data can be used to identify quicker resolutions and analysis because it includes check-in and locomotive data. Similarly, information about the number of passengers can be used to determine the number of buses that are needed as replacement transport.

Despite the importance of data to the operations of trains, the responsibility still relies on the people who maintain it. They need to guarantee safety to travellers’ data because the safety of individuals may be jeopardized if sensitive information falls into the wrong hands. If the wrong people get access to crucial data, it could present a massive breach of privacy. The current laws such as the GDPR have also necessitated extra security measures, as failure to secure customer data may have financial and legal implications.