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Smart city article details

Title	Machine Learning-Based Big Data Analytics In Smart Cities: A Survey Of Current Trends And Future Research Directions
ID_Doc	36039
Authors	Althabahi M.H.; Ahmad Jan M.; Brik B.; Foufou S.
Year	2024
Published	Proceedings - 2024 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2024
DOI	http://dx.doi.org/10.1109/BDCAT63179.2024.00040
Abstract	Efficient utilization of Big data in smart cities is crucial for smooth operation of urban environments. Machine learning-enabled big data analytics is essential for optimizing city operations, improving resource management, and enhancing the quality of urban life. By leveraging machine learning (ML) algorithms to process and analyze the vast amounts of data generated in smart cities, authorities can gain insights and make real-time data-driven decisions. This article provides a comprehensive survey of how ML techniques are applied to analyze the large volumes of data generated by smart cities to improve urban living. Various ML algorithms, such as supervised, unsupervised, and reinforcement learning (RL) are discussed by highlighting their roles in numerous applications. Moreover, their distinguishing features are examined, enabling the selection of the most suitable algorithms for various applications in smart cities. Finally, the survey explores various challenges and suggests numerous research directions. © 2024 IEEE.
Author Keywords	Big Data; Internet of Things; Machine Learning; Reinforcement Learning; Smart Cities; Supervised Machine Learning

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