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Title Exploring Data Science For Sustainable Urban Planning
ID_Doc 25509
Authors Radhakrishnan S.; Varshan P.S.; Lakshitha S.K.; Suganya R.
Year 2025
Published Cyber security and Data Science Innovations for Sustainable Development of HEICC: Healthcare, Education, Industry, Cities, and Communities
DOI http://dx.doi.org/10.1201/9781032711300-27
Abstract Data science assumes an indispensable and paramount role within the realm of smart cities and sustainable communities, where its transformative impact is notably conspicuous. Data-driven strategies emerge as linchpins in the realization of these objectives. Data science orchestrates the optimization of transportation systems, leveraging real-time data, predictive analytics, and machine learning for the precise management of traffic. It spearheads a revolution in waste management, capitalizing on sensor data, Internet of Things (IoT) technologies, and predictive models to streamline waste collection procedures, curtail the environmental footprint, and elevate operational efficiency. In tandem, data analytics and AI-powered solutions serve as bulwarks for public safety, bolstering emergency response mechanisms and prophylactic measures against criminal activities, thereby nurturing the evolution of urban spaces into smarter and more secure environments. These advancements encompass the implementation of intelligent lighting and the facilitation of community engagement. Through the comprehensive exposition of data science applications across these spheres, this work casts light upon how smart cities can harness these data-propelled strategies, thereby achieving superior outcomes in transportation, waste management, public safety, and the enrichment of urban lifestyles. It extends invaluable guidance to urban planners, policymakers, and technologists in their quest to harness data, fostering the development of more astute, sustainable communities. © 2025 selection and editorial matter, Thangavel Murugan and W. Jai Singh; individual chapters, the contributors.
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