Every day in London, about 6.5 million people use public bus lines to get around the city, and there are 3 million underground users as well. The TFL (Transport For London) was created by the Greater London Authority to manage this vast network of routes, personnel, services and maintenance operations (Including the city’s suburban train system).
The huge amount of data generated represents a goldmine for those who wish to analyze, in real time, levels of quality, as well as opportunities to improve routes, stations and many others facets of public transport. For this purpose, Big data technology is used to gather, store and later process data using analytics. This provides TFL a clearer picture regarding Londoners daily usage patterns with a variety of managed services (as well as the possibility of placing individual riders in different categories).
The data includes areas covered during the analytics phase, such as lines with greatest ridership as well as those with the greatest number of passengers who board or get off (with a view to improving services on these lines), broken down by section or zone, transfers made by riders and even inter modal transfers: bus, underground or commuter train services (given that many daily commutes require at least two such transfers).
According to the TFL analytics chief Lauren Sager-Weinstein, they can also provide individualized information on public transport riders. And this initiative is accepted nowadays by 83% of public transport users.
Original Source: Forbes Technology