Efficiency improving of emergency monitoring and forecasting based on the information system

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The article is devoted to the automated information system modification to solve monitoring and forecasting problems of natural and man-made emergencies in order to increase the efficiency of its functioning, namely, to increase the execution speed of the main operations, to reduce the error probability. Monitoring and forecasting of emergencies are among the priorities in the field of population from emergencies protection, as the prevention and elimination of their consequences are carried out on the basis of these tasks. At the same time, the data collection speed, processing and analysis largely determine the efficiency of the obtained results. The existing system of monitoring and forecasting of natural and man-made emergencies, its functional model in IDEF0 notation, characteristic features, advantages and disadvantages are considered. The existing system can be improved by automating a number of tasks related to the processing, transmission and storage of large data amounts, including real time data, as well as the generation of consolidated reports on the results of monitoring and forecasting of various objects. The information architecture of the solution reviewed and the corresponding database model form the basis of the proposed solution. The IDEF0 model of emergency monitoring and forecasting has been introduced taking into account the proposed modification of the automated information system. The main operation execution time comparative analysis based on the initial and modified automated information system (AIS) using the existing hardware confirms the effectiveness of the proposed solution. Data exchange and generation automation of consolidated reports on multiple monitoring objects will simplify analysis of the obtained results and solutions development based on them aimed at prevention of natural and man-made emergencies, as well as elimination of their consequences.

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Automated information system (ais), emergency monitoring and forecasting, automation, data conversion

Короткий адрес: https://sciup.org/148321980

IDR: 148321980   |   DOI: 10.31772/2587-6066-2020-21-3-323-332

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