Abstract
The collaborative emergency call-taking information system in the Czech Republic forms a network of cooperating emergency call centers processing emergency calls to the European 112 emergency number. Large amounts of various incident records are stored in the databases. The data can be used for mining spatial and temporal anomalies, as well as for the monitoring and analysis of the performance of the emergency call- taking system. In this paper, we describe a method for knowledge discovery and visualization targeted at the performance analysis of the system with respect to the organization of the emergency call-taking information system and its data characteristics. The method is based on the Kohonen Self-Organising Map (SOM) algorithm and its extension, the Growing Grid algorithm. To handle the massive data, the growing grid algorithm is implemented in a parallel environment using compute unified device architecture. Experimental results illustrate that the proposed method is very efficient.
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Snášel, V., Klement, P., Gajdoš, P., Abraham, A. (2013). Self Organising Maps on Compute Unified Device Architecture for the Performance Monitoring of Emergency Call-Taking Centre. In: Gavrilova, M.L., Tan, C.J.K., Abraham, A. (eds) Transactions on Computational Science XXI. Lecture Notes in Computer Science, vol 8160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45318-2_15
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