Ubiquitous community driven traffic analysis

Abstract

The availability data sources is increasing thanks to the rise of interconnected devices with sensory capabilities. Their use, has also become predominant in tasks that are not directly related with the devices' primary function or for which they may not even be designed for. Taking in consideration the act of driving, this research shows how through a composition of theories and services with these connected devices, it is possible to monitor and profile drivers performance and the generate community knowledge that can be used for the creation of user notification and warning systems. Thanks to the composition of theories from ubiquitous sensorization, machine learning, and communications it possible to design a general platform based on ubiquitous devices that generate information and models about each user behaviour individually and in communities around specific locations. This helps the improvement of not only performance but also security. Sensorization of large communities of users enrolled in driving activities can generate useful knowledge to the community. This article explores ubiquitous sensorization over the PHESS Driving platform to create reliable information that can be shared between users based on communication opportunity and location.