The article emphasizes the key role of information systems in the development of the environmental component of modern smart cities. It highlights that the implementation of IoT and Data Science technologies can significantly enhance the efficiency of monitoring and managing environmental parameters, which in turn allows for timely detection and response to environmental issues. This approach, combined with the use of intelligent information systems, can facilitate the prompt adoption of effective measures to eliminate and minimize negative impacts on the environment. A review of previous studies dedicated to the application of various information technologies and systems for optimizing the placement of resources, such as weather stations and environmental monitoring sensors, is conducted. It is substantiated that while linear and nonlinear methods provide accurate solutions, they require significant computational resources. Evolutionary algorithms offer flexibility, but their results can be less predictable. It is noted that evolutionary algorithms, such as genetic algorithms, demonstrate significant potential in solving tasks related to large data volumes. Machine learning method
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