DIRECTIONS OF APPLICATION OF THE SYSTEMS APPROACH IN THE SYSTEM OF STATE MANAGEMENT OF ENVIRONMENTAL SAFETY USING AEROSPACE TECHNOLOGIES
DOI:
https://doi.org/10.17721/3041-1912.2024/2-3/11Keywords:
aerospace technologies, public administration, environment and natural resources, environmental safety, environmental monitoring, management system, systemic approach, artificial intelligenceAbstract
Background. The topic of evaluating the application of a systemic approach in the system of state management of environmental security with the use of aerospace technologies became especially relevant for Ukrainian society with the beginning of the war, since military actions caused primary and transboundary impacts on the environment and natural resources and caused risks for ecosystems, the economy of Ukraine and beyond . Therefore, there is a need to join the European and world experience of assessing and restoring disturbed ecosystems by means of a systematic analysis of processes and phenomena in the environment and the formation and implementation of management decisions. This approach implies the need to first carry out environmental monitoring in order to investigate the causes and consequences of the impact on ecosystems, and then to synthesize management solutions aimed at ensuring environmental safety. The modern level of development of science and technology provides an opportunity to apply artificial intelligence systems in environmental safety management systems of regions, enterprises and organizations using aerospace technologies. The purpose of the work is to determine the areas of application of the systemic approach in the system of state management of environmental security with the use of aerospace technologies and the application of artificial intelligence.
Methods. The article uses a number of general scientific and special methods. Methods of system analysis, synthesis of management decisions were used to evaluate scientific research and legal acts regarding the formation and functioning of the environmental safety management system; methods of remote data processing, multispectral space images; methods of geospatial modeling, mathematical statistics.
Results. The peculiarities of building environmental safety management systems with the use of artificial intelligence and aerospace technologies are analyzed. Currently, the proposed approach of comprehensive assessment of disturbed ecosystems using artificial intelligence is developed and tested in different territories, different types of ecosystems and different data sources, in particular, a demonstration example is presented in this article as well. The use of an environmental safety management system with an intelligent subsystem for supporting the adoption of managerial environmental decisions will be quite useful for the post-war recovery of the territory of Ukraine, environmental protection, balanced environmental management and sustainable development. Further research should be focused on the application of intelligent support systems for making managerial environmental decisions to eliminate environmental risks and improve environmental safety. With the use of a systemic approach, environmental solutions in artificial intelligence systems are considered as a systematic combination of informational, organizational and operational solutions that relate to the following areas of environmental protection and natural resources: assessment and forecasting of the state of atmospheric air; assessment and forecasting of climate change; assessment and forecasting of the state of water resources; assessment and forecasting of the state of biological and landscape diversity, the development of the nature reserve fund and the formation of the national ecological network; assessment and forecasting of the state of land resources and soils; assessment and forecasting of the state of the subsoil; assessment and forecasting of the state of waste management; assessment of the state of objects that pose an increased environmental hazard; assessment and forecasting of the state of industry and its impact on the environment; assessment and forecasting of the state of agriculture and its impact on the environment; assessment and forecasting of the state of energy and its impact on the environment; assessment and forecasting of the state of transport and its impact on the environment; assessment and forecasting of the state of sustainable consumption and production; development of recommendations for state management in the field of environmental protection. Conclusions. The development and implementation of state and regional (industry) environmental safety management systems is possible by applying a systemic approach using aerospace technologies. Such systems should perform the following functions: obtaining environmental information in real time, processing this information, predictive modeling of environmental processes, determining environmental risks (in space and time), providing proposals and recommendations for eliminating adverse environmental situations according to specified indicators (criteria for the effectiveness of the management system). The application in the environmental safety management system involves the implementation of environmental monitoring through a comprehensive remote assessment of the state of disturbed ecosystems and conducting a geospatial analysis of the relevant risks. The use of artificial intelligence is an important, flexible, convenient and useful tool for managing and planning the development of territories. Remote sensing methods using aerospace technologies are of particular importance in the context of large-scale hostilities currently taking place in Ukraine. In many cases, only remote methods using artificial intelligence are able to provide reliable predictive information about the state of ecosystems that are inaccessible or dangerous for ground-based research. The methodological basis of the study of the problem of the formation of the system of management of ecological safety of the environment and natural resources, objects of critical infrastructure should be an intellectual support system for making management ecological decisions, the development of special research methods aimed at obtaining objective and reliable results. Using a systemic approach, environmental solutions in artificial intelligence systems are considered as a systematic combination of informational, organizational and operational solutions related to the protection of the environment and natural resources.
References
Bondar, O. I., Mashkov, O. A., Prysiazhniy, V. I., Ovodenko, T. S., & Pechenyi V. L. (2023). The concept of creating an intelligent information system to support decision-making in the field of environmental safety, Ecological sciences: a scientific and practical journal, DEA, 3(48), 7–16 [in Ukrainian].
Bondar, O. I., Mashkov, O. A., Prysiazhniy, V. I., Ovodenko, T. S., & Pechenyi V. L. (2023). The paradigm of information processing in an intelligent information system to support decision-making in the field of environmental safety, Ecological sciences: a scientific and practical journal. DEA, 4(49), 144–152 [in Ukrainian].
Durnyak, B., Babichev, S., & Yasinska-Damri, L. (2022). Application of convolutional neural networks in big data classification systems. Computer technologies of printing, 1(47), 8−20 [in Ukrainian].
Mashkov, O. A., Ivashchenko, T. G., Mukhin, E. A., Mukhina, K. E., Trysnyuk, V. M., & Chumachenko, S. M. (2023). System approach in environmental sciences: systemic ecological analysis and synthesis of management ecological solutions, Serednyak T. K., 642, ISBN 978-617-8245-31-3 [in Ukrainian].
Mashkov, O. A., Ivashchenko, T. G., Mukhina, K. E., & Pechenyi, V. L. (2023). Integration of aerospace technologies into the environmental safety management system: evaluation of the effectiveness of the application of the support system for making managerial informational environmental decisions, Environmental safety and environmental protection technologies: scientific journal, 4, 20-27 [in Ukrainian].
Nils, J., Nilsson. (2009). The Quest for Artificial Intelligence. Cambridge University Press, 1, 578, ISBN 978-0521116398.
Oghirko, I. V., Yasinskyi, M. F., & Yasinska-Damri, L. M. (2015). Hard and soft mathematical models and their application. Scientific notes [of the Ukrainian Academy of Printing], 1 (15), 102−117 [in Ukrainian].
Shakhovska, N. B., Kaminsky, R. M., & Vovk, O. B. (2018). Artificial intelligence systems, Publishing House of Lviv Polytechnic, 392,
ISBN 966-941-197-6 [in Ukrainian].
Stepashko, V. S. (2010). Elements of the theory of inductive modeling. Status and prospects of the development of informatics in Ukraine, Naukova Dumka, 471−486 [in Ukrainian].
Stuart, J., Russell, & Peter, Norvig. (2015). Artificial Intelligence:
A Modern Approach. Pearson, 3, ISBN 978-9332543515.
Tegmark, Max. (2019). Life 3.0: the age of artificial intelligence, Nash format, 432, ISBN 978-617-7682-99-7 [in Ukrainian].
Tkachenko, R. A., Kustra, N. A., Pavlyuk, O. M., & Polishchuk, V. V. (2014). Means of artificial intelligence, National Lviv University. polytechnic, View of Lviv. polytechnics, 204, ISBN 978-617-607-692-6 [in Ukrainian].
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