Methodology for Automatic Detection of Emergency Situations at Public Transport Objects
Abstract
The presented work is devoted to the development of an information and measuring system for identifying emergency situations arising at public transport facilities. This paper presents statistics on the most common types of emergency situations occurring at public transport facilities. The paper considers a limited set of, the most common, emergency situations, automatic selection of which is possible at the present stage of science and technology.
A method for classifying emergency situations in a continuous stream of images is proposed. This method is based on the use of a fuzzy classifier based on a fuzzy model based on the Mamdani algorithm. To improve the quality of the classifier, the method for measuring the parameters of emergency situations was modernized in order to exclude from the analysis objects present in the image that are obviously of no interest. To do this, each moving object present at a given moment in time on the scene was subjected to a classification procedure based on a dynamic feature vector. In order to further increase the number of contingencies, the method of classifying contingencies in the continuous flow of images includes two stages: 1) detection of the withdrawal of certain values of the feature vector components outside the defined values; 2) a method for identifying/classifying emergency situations.
Testing of the proposed classification method and experimental testing confirmed its effectiveness.
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