The incredible progress witnessed in geographic information and pervasive systems equipped with positioning technologies have motivated the evolving of classic data towards mobility or trajectory data resulting from moving objects' displacements and activities. Provided trajectory data have to be extracted, transformed and loaded into a data warehouse for analysis and/or mining purposes; however, this later, qualified as traditional, is poorly suited to handle spatio-temporal data features and to exploit them, efficiently, for decision making tasks related to mobility issues. Because of this mismatch, we propose a bottom-up approach which offers the possibility to model and analyse the trajectories of moving object activities in order to improve decision making tasks by extracting pertinent knowledge and guaranteeing the coherence of provided analysis results at the lowest cost and time consuming. We illustrate our approach through a creamery trajectory decision support system.
['Noura Azaiez', 'Jalel Akaichi']
How trajectory data modeling improves decision making