London has approximately 8.6 million population, which will rise to 10 million according to the prediction, on a daily basis there are 24 million journeys (from A to B) made across the city on buses, tubes, boats and cable cars. This whole traffic management system is administrated by Transport for London (known as TfL). 27,000 stuffs are working for the public organization to keep London moving.
With the increase in the number of population and number of journeys per person, it has been very difficult to manage the massive system seamlessly. TfL has deployed SAP HANA to manage the traffic flow more efficiently.
There has been a need of business intelligence system which could understand the data collected from IoT devices attached to trains, buses, streets and could process the massive unstructured data known as Big Data in real time. Also, it should produce an insight of the information collected to help in making better decisions.
SAP HANA is the best fit for the requirement, with the power of in-memory computing it leverages real time analysis and its compatibility towards the SAP ERP makes it most effective data processing platform. Moreover, HANA comes with predictive analytics which would help TFL to understand the metrics of traffic flow like number of public transports required in rush time, right time for more train allocation, no of busy routes and which are they etc. Even capturing small information like humidity in air (when it's going to rain), most used train stations for arrival or departure, where accelerators or brakes are used heavily and processing them using SAP HANA Platform the whole traffic system could be optimized. Moreover, it reduces tons of effort and saves time.