Mobility: mastering context is the key…
So far, we have explored two major concepts related to mobility: context awareness and tra jectories. In the ﬁve next years, we intend to reinforce our approach and results by taking the following research directions:
- Investigating information retrieval and Web mining techniques, coupled with context-awareness (i.e. knowledge about the user and the physical and material environments) and augmented reality, in order to bring mobile users relevant (and even sometimes vital) information and better knowledge about the surroundings.
- Context can also be used when mining Big Data of user-generated contents coming from social networks. Pattern mining algorithms can be used to extract relations and then conﬁrm or invalidate hypotheses, for instance about the link between what people eat, how they feel and the place where they live (T. Moreira’s PhD thesis started in 2014).
- Sensors or actuators, whether they are static, agile or mobile are data sources that may be requested on demand, not simply continuously. More generally, data collection can be integrated into a producer-consumers schema where a producer (for instance one municipality) would launch a citizen (consumers or sensors) survey on the basis of several criteria (places in the city, periods of time, socio-professionnal categories, etc.) with regard to a given urban planning pro ject. Designing and building an infrastructure that optimizes such a spatiotemporal data collection problem is a research way we intend to investigate. Such data collection problems are nowadays omnipresent: they can also be found in mobile crowdsourcing market systems where mobile workers are recommended some tasks they are able to accomplish (A. Sales Fonteles’s Phd, started in 2013).
- Mining trajectories consists of ﬁnding patterns in order to exhibit some trajectory behaviour. Here, context-awareness is a key asset for determining mobile users context-based behaviour, and then for predicting mobiles user behaviour depending on various situations and circumstances. (T. Paiva Noguera’s PhD started in 2012). Trajectories can also be more virtual as soon as socio-economical or cultural or ethical factors are considered, and we have just started to investigate ways to acquire, represent, query, analyse, and visualize the underlying abstract notion of life trajectory.