Abstract
Semantic interpretation of monitored scenes implies the well-known problem of linking physical signals received by sensors with their meaning for a human. Our line of work aims to develop a global architecture, which we call “Architecture for Semantic Interpretation of Monitored Scenarios (ASIMS)”, to integrate all the information processing abstraction levels, from the sensory agent process and coherent fusion of agent results to behaviour and situation identification. This work presents a specific structure for the acquisition and fusion of events from the object level, which forms part of the global ASIMS structure. In remote processing nodes, events caused by variations in magnitudes in the common data model are identified via finite automata models. These events are merged by the central node to solve the usual problems of centralised systems: synchronisation, redundancy, contradiction and heterogeneity of the information that they receive from different sources. For this we have broken down the fusion mechanism into three stages: Synchronisation, Standardisation and Fusion, which are described in the article with simple examples.
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Rivas-Casado, Á., Martínez-Tomás, R. (2011). Event Detection and Fusion Model for Semantic Interpretation of Monitored Scenarios within ASIMS Architecture. In: Ferrández, J.M., Álvarez Sánchez, J.R., de la Paz, F., Toledo, F.J. (eds) Foundations on Natural and Artificial Computation. IWINAC 2011. Lecture Notes in Computer Science, vol 6686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21344-1_54
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DOI: https://doi.org/10.1007/978-3-642-21344-1_54
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