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Smart city article details

Title	Predictive Analytics For Smart City Infrastructure: Leveraging Iot And Machine Learning For Real-Time Decision-Making
ID_Doc	42871
Authors	Bhutani M.; Gulzar Y.; Reegu F.A.; Ayoub S.
Year	2025
Published	Lecture Notes in Networks and Systems, 1294 LNNS
DOI	http://dx.doi.org/10.1007/978-981-96-3253-4_46
Abstract	Therefore, this paper looks at the ways in which predictive analytics has the potential to revolutionize the design of smart city systems through IoT and the application of machine learning for real-time decision-making. Combined with the growth of complexity in urban environments, predictive analytics can enhance several aspects of life in cities, such as traffic, safety, power supplies, and emissions. Abundant data from the IoT devices, along with enhanced analytical models make predictive analytics a useful tool in directing the city administrators’ operations. The paper outlines the major applications, data handling techniques, and real-time analysis paradigms required to incorporate prediction functionality into city systems. It also tackles issues like data privacy, when it is expandable and when and where it cannot work due to technical issues and other useful topics like blockchain, quantum computing, etc. These results indicate that there is great potential for the usage of predictive analytics to build progressive, cost-effective, and robust smart cities. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Author Keywords	Data privacy; IoT; Machine learning; Predictive analytics; Real-time decision-making; Smart cities; Sustainability; Urban infrastructure

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