Database Reference
In-Depth Information
City traffic
Maritime
Air traffic
Animals'
movement
Human
movement
Applications
Interpretation
visualization
Privacy-aware
Data mining
GeoKnowledge
Aggregations/
transformations
Trajectory
reconstruction
Patterns,
semantic behaviors
Trajectory Data
Warehouse
Trajectory
Database
Privacy enforcement
Figure 2.1 The big picture of moving object data management, warehousing, and mining
concepts.
informative abstractions of the portions of the trajectories transmitted so far), as
well as techniques to handle missing/erroneous values. Moreover, to deal with
moving object applications that are restricted to some network, map-matched
trajectories may be needed. In other words, we may need the specific trajectory
points and portions to correspond to valid network paths. This may include,
for example, performing preprocessing or postprocessing tasks that do not vio-
late the validity of trajectories in terms of the real underlying network. We
describe these kinds of tasks as trajectory data handling and we present them in
Section 2.3 .
In Section 2.4 , we present trajectory reconstruction techniques for transform-
ing sequences of raw sample points into meaningful trajectories and store them
in trajectory databases. The reconstructed trajectories can be either semantic-free
(raw trajectories) that just represent the movement of an object or semantically
enriched, containing information about the nature of the movement.
Section 2.5 presents techniques for the privacy-preserving collection of tra-
jectory data.
2.2 Tracking Trajectory Data
In this section, we present some technologies that can be used for tracking
trajectories of moving objects. More specifically, these technologies provide
us access to position data that may represent an incomplete, partial, or vague
representation of the real movement of moving objects but with the appropriate
handling techniques (Section 2.3 ) can lead to the reconstruction of trajectories
(Section 2.4 ).
Search WWH ::




Custom Search