DEVELOPMENT OF A METHOD OF COMPLETING EMERGENCY RESCUE UNITS WITH EMERGENCY VEHICLES
Authors/Creators
- 1. National University of Civil Defence of Ukraine
- 2. Kharkiv National University of Internal Affairs
- 3. National Academy of the National Guard of Ukraine
Description
The study considers the process of response of emergency rescue units to emergencies and hazardous events occurring on the territory of a city with a population of more than one million people. It has been determined that the flow of calls to the departments of emergency rescue units has a certain structure, and their number correlates with the size of the total area of the housing stock of a settlement. This dependence was described by a polynomial trendline, for which an appropriate equation was composed to determine the number of calls that could be made to the emergency rescue units in the future. These data can also be used to determine the number of emergency vehicles that emergency response units must provide to carry out their intended operations effectively. A method of completing the departments of emergency rescue units with emergency vehicles is proposed taking into account the operational situation in the areas of their on-site visits, and it consists in performing four consecutive stages. The first stage involves the selection of the necessary factors on the basis of analysing statistical data that characterize the process of response of departments of emergency rescue units to various destructive events and the construction of a predictive model. The second stage involves the calculation of the indicator of the specific number of emergency vehicles per call, taking into account the different groups of call flows. The third stage involves determining the total number of emergency vehicles at the emergency rescue units of a settlement. As the mathematical models applied at this stage are based on the Poisson distribution law, there is a limitation in using the proposed method, entailing that the flow of calls must be Poisson. The fourth stage of the calculations involves the redistribution of the previously determined total number of emergency vehicles between the departments of the emergency rescue units, taking into account the peculiarities of the operational situation in the areas of their on-site visits.
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Additional details
References
- Kokhanenko, V., Belyaev, V. (2017). The principle of complete setting of departments of fire-and-saving parts in the settled points of Ukraine by accounting the conditions of operation. Problemy pozharnoy bezopasnosti, 41, 98–103.
- Tiutiunyk, V. V., Ivanets, H. V., Tolkunov, I. A., Stetsyuk, E. I. (2018). System approach for readiness assessment units of civil defense to actions at emergency situations. Scientific Bulletin of National Mining University, 1, 99–105. doi: https://doi.org/10.29202/nvngu/2018-1/7
- Shkurnov, S. A. (2016). Informatsionno-analiticheskaya model' prinyatiya resheniy po pereosnashcheniyu parka pozharnyh avtomobiley. Pozharovryvobezopasnost', 25 (7), 58–62.
- Martinovich, N. V., Tatarkin, I. N., Antonov, A. V., Melnik, A. A. (2015). Methodology for identification of fire-rescue subdivision demand in the fire-service machinery and firefighting equipment. Naukovedenie, 7 (6), 1–12.
- Tracey, J. A., Rochester, C. J., Hathaway, S. A., Preston, K. L., Syphard, A. D., Vandergast, A. G. et. al. (2018). Prioritizing conserved areas threatened by wildfire and fragmentation for monitoring and management. PLOS ONE, 13 (9), e0200203. doi: https://doi.org/10.1371/journal.pone.0200203
- Larin, O. M., Kalynovsky, A. Y., Kovalenk, R. I. (2016). Development of methods for determining the size of the vehicle fleet in firerescue units. Komunalne hospodarstvo mist, 130, 92–100.
- Aldabbas, M., Venteicher, F., Gerber, L., Widmer, M. (2018). Finding the Adequate Location Scenario After the Merger of Fire Brigades Thanks to Multiple Criteria Decision Analysis Methods. Foundations of Computing and Decision Sciences, 43 (2), 69–88. doi: https://doi.org/10.1515/fcds-2018-0006
- Wang, J., Liu, H., An, S., Cui, N. (2016). A new partial coverage locating model for cooperative fire services. Information Sciences, 373, 527–538. doi: https://doi.org/10.1016/j.ins.2016.06.030
- Bandyopadhyay, M., Singh, V. (2016). Development of agent based model for predicting emergency response time. Perspectives in Science, 8, 138–141. doi: https://doi.org/10.1016/j.pisc.2016.04.017
- Popelínský, J., Vachuda, J., Veselý, O. (2017). Geographical modelling based on spatial differentiation of fire brigade actions: A case study of Brno, Czech Republic. Bulletin of Geography. Socio-Economic Series, 35 (35), 81–92. doi: https://doi.org/10.1515/bog-2017-0006
- Krasuski, A., Kreński, K. (2014). Decision Support System for Blockage Management in Fire Service. Studies in Logic, Grammar and Rhetoric, 37(1), 107–123. doi: https://doi.org/10.2478/slgr-2014-0020
- Brushlinsky, N., Sychev, Y. (2015). Organization of industrial parks complex safety and security system maintenance nowadays. Pozhary i chrezvychaynye situatsii: predotvrashchenie, likvidatsiya, 1, 54–60.
- Clarke, A., Miles, J. C. (2012). Strategic Fire and Rescue Service decision making using evolutionary algorithms. Advances in Engineering Software, 50, 29–36. doi: https://doi.org/10.1016/j.advengsoft.2012.04.002
- Kalynovsky, A. Ya., Kovalenko, R. I. (2017). Statistical study of the nature of hazardous events which are in the Kharkov city. Komunalne hospodarstvo mist, 135, 159–166.
- Usanov, D., Guido Legemaate, G. A., van de Ven, P. M., van der Mei, R. D. (2019). Fire truck relocation during major incidents. Naval Research Logistics (NRL), 66 (2), 105–122. doi: https://doi.org/10.1002/nav.21831
- Luokkala, P., Virrantaus, K. (2014). Developing information systems to support situational awareness and interaction in time-pressuring crisis situations. Safety Science, 63, 191–203. doi: https://doi.org/10.1016/j.ssci.2013.11.014
- Sadeghi-Naini, A., Asgary, A. (2013). Modeling number of firefighters responding to an incident using artificial neural networks. International Journal of Emergency Services, 2 (2), 104–118. doi: https://doi.org/10.1108/ijes-03-2012-0001
- Brenych, Ya. V., Tymoshchuk, P. V. (2012). Neural network methods of solving of classification problem. Naukovyi visnyk NLTU Ukrainy, 22.13, 343–349.
- Kovalenko, R. I. (2017). Rozrobka sposobu vyznachennia neobkhidnoi chyselnosti bahatofunktsionalnykh mobilnykh avariyno-riatuvalnykh kompleksiv konteinernoho typu dlia komplektuvannia avariyno-riatuvalnykh formuvan. Naukovyi visnyk: tsyvilnyi zakhyst ta pozhezhna bezpeka, 2 (4), 40–46.