Abstract
Ubiquitous computing has changed the acquisition of mobility data, with two aspects contributing: the high penetration rate and the ability to capture and share information on a continuous basis. This applies to geolocation information, operational mobile phone data, and also, social network crowdsourced information. Additionally, under the umbrella of the Internet of Things trend, the deployment of the Connected Vehicle (Car-as-a-sensor) concept, supported by advanced V2X communications, provides massive data volume. For all these cases, data are open to never before seen opportunities to analyze and predict individual and aggregated mobility patterns. Big Data refers to the processsing capabilities of such an explosion in the amount, quality, and heterogeneity of available data. This chapter will review the most relevant data sources, introduce the underlying techniques supporting the BigData paradigm and, finally, provide a list of some relevant applications in the transport and mobility domain.
| Original language | English |
|---|---|
| Title of host publication | Intelligent Vehicles |
| Subtitle of host publication | Enabling Technologies and Future Developments |
| Publisher | Elsevier |
| Pages | 175-205 |
| Number of pages | 31 |
| ISBN (Electronic) | 9780128128008 |
| ISBN (Print) | 9780128131084 |
| DOIs | |
| Publication status | Published - 1 Jan 2017 |
Keywords
- Applications
- Bigdata
- Data
- FCD
- Machine learning
- Processing architectures