As the world’s population living in metropolitan areas increases, so increases the need for effective and sustainable interventions and services to inject mobility intelligence and improve the quality of life in large urban environments. The technological developments have resulted in the collection of unknown volumes of data across systems that’s are operating in the transport, mobility and the urban applications domains.
The existing accumulated large volumes of data, known as “big data”, are generating a strong interest in the research communities, the relevant industries and among policy makers. There is a strong demand for efficient and scalable smart services, but that imposes new requirements to better exploit the immense and continuously rising amounts of data, generated by industrial operations, sensors and devices (Internet of Things – IoT), social media and often aggregated Open Data sources.
To develop novel applications and services and to create new operational business models Big Data research requires a multi-disciplinary approach. In order to transform the voluminous and incomprehensible data into intelligence and knowledge the new approach will bring together research actors, customers’ demand and business field experts, infrastructure operators, and software industry actors . The business impact of Big Data is starting to take form in many business fields, e.g.
- Transport & Mobility: intelligent transportation, mobility as a service (MaaS), car as a service (Caas), pay as you drive, adaptable insurance services, smart pricing …
- Finance & Insurance: data-consuming verticals
- Health-care: where Big Data and IoT solutions are improving cost-efficiency, performance and quality of patient care services
Still, however, innovation is held back by limitations of current Big Data processing methods and infrastructures as in most cases smart services remain uncoupled and isolated.