Smart City Gnosys
Smart city article details
| Title | Design Of An Intelligent System For Enhancing Urban Social Resilience |
|---|---|
| ID_Doc | 18798 |
| Authors | Lipianina-Honcharenko K.; Komar M.; Madarash R.; Novosad S.; Zhabiuk V.; Mykhalchuk N.; Koshytskyi K.; Lendiuk D.; Melnyk N.; Telikhovskyi O. |
| Year | 2024 |
| Published | Eastern-European Journal of Enterprise Technologies, 6, 13(132) |
| DOI | http://dx.doi.org/10.15587/1729-4061.2024.317717 |
| Abstract | This paper considers a comprehensive approach to the use of intelligent systems in the context of smart cities, which is aimed at increasing their social sustainability under the conditions of growing urbanization and globalization. Cities face challenges related to the need to optimize the management of urban resources and improve the quality of life of residents, which requires innovative approaches to planning and the use of advanced technologies. The proposedintelligentsystem architecture, integrating six modules such as quality of life modeling, socio-economic analysis, intelligent tourism, environmental monitoring, legal interpretation, and misinformation detection, has demonstrated a 25–40 % performance improvement depending on the module. The effectiveness of the proposed system is explained by the use of advanced algorithms of machine learning and data analysis, which makes it possible to reduce the time of solving critical tasks and increase the adaptability of the city infrastructure to future challenges. Owing to the integration of intelligent systems into city management, cities gain the ability to respond more effectively to current and projected social and environmental challenges, significantly improving the quality of life and environmental sustainability. The proposed system could be implemented in cities of different sizes and configurations, contributing to long-term socio-economic development and environmental sustainability. Effective implementation of the system reduces city management costs by up to 30 %, while reducing CO2 emissions by 10–15 %, which is important in the context of combating climate change © (2024), (Technology Center). All rights reserved. |
| Author Keywords | intelligent systems; machine learning; modeling; smart cities; socio-economic analysis |
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