This paper describes an overview of the architecture of an evaluated multiscreen experience based on MotoGP sports content, which was developed using an object-based broadcasting approach. This architecture enables experiences to be implemented as distributed media applications consisting of components orchestrated by a cloud-hosted service platform. The MotoGP service prototype was evaluated by more than 90 MotoGP fans, and assessments of the features and the experience have been broadly positive.

This demonstration will showcase a new approach to the production and delivery of multi-screen entertainment enabled by an innovative, standards-based platform developed by the EU-funded project 2-IMMERSE. Object-based production enables engaging and interactive experiences which make optimal use of the devices available, while maintaining the look and feel of a single application. The "Theatre at Home" prototype offers an enhanced social experience for users watching a live or "as live" broadcast of a theatre performance, allowing them to discuss it with others who are watching at the same time, either in a different room or in a different home.

This demonstration will showcase a new approach to the production and delivery of multi-screen entertainment enabled by an innovative, standards-based platform developed by the EU-funded project 2-IMMERSE. Object-based production enables engaging and interactive experiences which make optimal use of the devices available, while maintaining the look and feel of a single application. The "Theatre at Home" prototype offers an enhanced social experience for users watching a live or "as live" broadcast of a theatre performance, allowing them to discuss it with others who are watching at the same time, either in a different room or in a different home.

One of the greatest concerns related to the popularity of GPS-enabled devices and applications is the increasing availability of the personal location information generated by them and shared with application and service providers. Moreover, people tend to have regular routines and be characterized by a set of “significant places”, thus making it possible to identify a user from his/her mobility data. In this paper we present a series of techniques for identifying individuals from their GPS movements. More specifically, we study the uniqueness of GPS information for three popular datasets, and we provide a detailed analysis of the discriminatory power of speed, direction and distance of travel. Most importantly, we present a simple yet effective technique for the identification of users from location information that are not included in the original dataset used for training, thus raising important privacy concerns for the management of location datasets.