Big Data and the IoT Helps London Public Transport

November 7, 2015

London is well known as one of the busiest cities in the world, with a current population of 8.6 million and expected to grow to 10 million within the next few years (and this is not including the constant influx of tourists). Transport for London (TfL) makes it possible for these millions to get around the city, running a network of footpaths, roads, cycle paths, buses, trains, taxis, and even ferries. Running these paths, that so many use daily, gives TfL access to huge amounts of data from ticketing systems, sensors, surveys, focus groups, and social media.

The rapid growth happening makes it integral to constantly improve the structure of the network, which is becoming easier than ever through big data and the Internet of Things (IoT). The question becomes, how can TfL use this data to create the most efficient system in this hugely populated city?

A World of Data

One example of the ways TfL is collecting data in London is with the Oyster prepaid travel cards. Oyster is a smartcard which can hold pay as you go credit, Travelcard and Bus & Tram Pass season tickets. You can use it to travel on bus, Tube, tram, DLR, London Overground, TfL Rail and most National Rail services in London. However, these Oyster cards are doing more than allowing passengers to load money onto them to travel seamlessly around the city- they are offering a world of data to the system. This data includes the amount placed on the card, the card carrier’s information, the frequency of use, travel routes, types of transport, and so much more.

This data is then analyzed and used to create maps presenting when are where people are traveling, for both a more accurate bigger picture and a better analysis of individual journeys. Seeing as most London journeys involve more than one method of transportation, being able to analyze the journey as a whole with this data, rather than in separate legs, is groundbreaking.

Creating Efficiencies

Other than analyzing journeys to predict traffic and determine efficiencies, data from TfL is also being used to manage disrupted schedules, offer personalized news, show travel needs, and much more. Rather than letting unexpected events and delays slow or even halt transportation, the data collected allows officials to fix the problem, send replacements, and even send information about the delay directly to one’s phone. Updates, changes in travel, and customized specials sent directly to the user allows the user to become a part of the process- overall making the customer experience much better.

So far, TfL has done an outstanding job in using their huge amount of data to identify the most major needs in transportation and implement changes that promote efficiency and ease of use. Improvements are continuing to be made, and big data and the Internet of Things will continue to take these improvements even further!


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