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Smart city article details

Title	Integrating Machine Learning And Iot: Pioneering Solutions For Sustainable Smart Cities
ID_Doc	32032
Authors	Pavanalaxmi; Kripa; Nayak R.; Abhishek A.B.; Praveen Kumar M.
Year	2025
Published	Springer Tracts on Transportation and Traffic, 22
DOI	http://dx.doi.org/10.1007/978-3-031-87627-1_3
Abstract	Smart cities are changing due to machine learning (ML) and the Internet of Things (IoT), advancing liability, sustainability, and increased efficiency. They maximise urban services, from public safety and environmental monitoring to transportation and energy management, using machine learning algorithms and interconnected IoT devices. Through predictive maintenance, anomaly detection, and sophisticated analytics, the integration of ML expands the possibilities of IoT systems. By detecting and notifying authorities of odd activity or possible security risks, incorporating surveillance systems with ML can improve crime prevention and response. ML algorithms examine this data to enhance efforts to create a healthier and cleaner urban environment by offering insights into pollution trends and health hazards. Significant infrastructure and technological investments are also required to deploy and keep these cutting-edge systems. Government agencies, stakeholders in the corporate sector, and society must work together effectively to address these issues and guarantee data’s secure and moral use. In summary, the development of smart cities depends on the fusion of machine learning and the IoT. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Author Keywords	IoT; Sensors; Smart city

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