Characterising the Next Generation of Mobile Applications Through a Privacy-Aware Geographic Knowledge Discovery Process

Renso C.

Spatio temporal data mining 

The proliferation of mobile technologies for 'always-on' at 'any-time' and 'anyplace' has facilitated the generation of huge volume of positioning data sets containing information about the location and the movement of entities through the geographic environment. In principle, every time an entity moves through space, it creates a trajectory (i.e. track or path) representing the history of its past and current locations. Examples of interesting trajectories of moving entities may range from hurricane and tornado tracks [19] to individual trajectories of animals [26] and planes [5]. Specially designed sensors can provide the location of a mobile entity as well as information about the geographic environment where this entity is moving. Current research on mobile technologies such as sensor web, wireless communication and portable computers has been crucial for the development of multi-sensor systems. Their use to sense a geographic environment and mobile entities can include photodiodes to detect light level, accelerometers to provide tilt and vibration measurements, passive infrared sensors to detect the proximity of humans, omni-directionalmicrophones to detect sound and other built-in sensors for temperature, pressure, and CO gas [9].

Source: Mobility, Data Mining and Privacy: Geographic Knowledge Discovery, pp. 39–70. Berlin: Springer-Verlag, 2007

Publisher: Springer-Verlag, Berlin, DEU