Improving the structure of the decision support information system

Roman Kovalenko

National University of Civil Defence of Ukraine

https://orcid.org/0000-0003-2083-7601

Andrii Kalynovskyi

National University of Civil Defence of Ukraine

http://orcid.org/0000-0002-1021-5799

Borys Kryvoshei

National University of Civil Defence of Ukraine

http://orcid.org/0000-0002-2561-5568

Ghryghorij Korotenko

Dnipro University of Technology

https://orcid.org/0000-0003-3774-5260

DOI: https://doi.org/10.5281/zenodo.4400194

Keywords: emergency rescue formation, information system, humanitarian aid, emergency, dangerous event

Abstract

The paper considers the process of functioning of information systems to support decision-making by the management of emergency response. The main advantages and disadvantages of known information systems are determined. It has been established that none of the analyzed systems provides full information support when making decisions to the emergency management leadership regarding the amount of necessary humanitarian aid to the affected population and possible ways of delivering these goods. The functionality of the previously mentioned information system has been determined, in particular, a function has been added that helps in resolving issues of providing humanitarian assistance to the affected population. The logical architecture of the information system for decision-making support during emergency response has been improved, which consists of four databases, a knowledge base, a decision module and a geographic information system module. The knowledge base of the information system has an algorithm that allows you to determine the commodity-nomenclature structure of humanitarian cargo consignments, as well as their sizes. In conditions of minor damage to the road surface and bridges, it is possible to deliver goods by road, and in conditions of their significant destruction by air. The decision-making module first assesses the possibility of delivering cargo by road, as an alternative to aviation, which ultimately reduces the cost of providing humanitarian assistance to the population affected by the emergency. The application of the multimodal transport method for the delivery of humanitarian cargo consignments is proposed. The efficiency has been evaluated and it has been established that with the method of direct transportation by helicopter, the delivery time is more than 31 % less than during combined transportation. At the same time, fuel consumption in case of multimodal transportations is almost 75 % less than during direct transportations using a helicopter.

References

1. 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. Visnyk Natsionalnoho Hirnychoho Universytetu, 1, 99-105.
2. Wu, X., Wu, L. (2011). Evaluation of the Fire Emergency Rescue Capability in Urban Community. Procedia Engineering, 11, 536-540.
3. Vlasov, K. S., Denisov, A. N. (2016). Metodika analiza pokazateley operativnogo reagirovaniya pozharno-spasatelnyih podrazdeleniy. Tehnologii tehnosfernoy bezopasnosti, 3(67), 207-213.
4. 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.
5. Pieter, L. van den Berg, Guido, A. G. Legemaate, Rob D. van der Mei. (2017). Increasing the Responsiveness of Firefighter Services by Relocating Base Stations in Amsterdam. INFORMS PubsOnLine, 47, 352-361.
6. Kovalenko, R. I. (2017). Improvement of the method of determining the number and nomenclature of the park of cars in fire-related surfaces of the city at the example of the city of Kharkov. East European Scientific Journal, (25), 48-56.
7. Krasuski, A., Krenski, K. (2014). Decision Support System for Blockage Management in Fire Service. Studies in Logic, Grammar and Rhetoric, 37(50), 107-123.
8. Xing, Z., Gao, W., Zhao, X., Zhu, D. (2013). Design and Implementation of City Fire Rescue Decision Support System. Procedia Engineering, 52, 483-488.
9. Mainak, B., Varun, S. (2016). Development of agent based model for predicting emergency response time. Perspectives in Science, 8, 138-141.
10. Kalіnovskiy, A., Kovalenko, R. (2018). Udoskonalennia matematychnoi modeli otsinky chasu reahuvannia pidrozdiliv na nadzvychaini sytuatsii. Problemy nadzvychainykh sytuatsii, 27, 31-38.
11. Kalіnovskiy, A., Kovalenko, R. (2017). Statystychne doslidzhennia kharakteru nebezpechnykh podii, yaki vynykaiut v misti Kharkovi. Komunalne hospodarstvo mist, 135, 159-166.