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Title	Bike Sharing Systems: A Green It Application For Smart Cities
ID_Doc	12178
Authors	Maniyar K.N.; Verma J.P.; Sharma N.
Year	2024
Published	Green Computing for Sustainable Smart Cities: A Data Analytics Applications Perspective
DOI	http://dx.doi.org/10.1201/9781003388814-10
Abstract	The need to apply “green IT research” practices is emphasized in this chapter, which also examines the role of the Internet of Things (IoT) in the creation of smart cities. A brief explanation of the green IoT idea is provided, along with a few methods for realizing it. The study then examines a number of green IoT applications, emphasizing the potential advantages of integrating eco-friendly procedures into IoT systems. The chapter offers a brief overview of the bike sharing programme and its difficulties. The major goal is to demonstrate how several regression models, including linear regression, random forest, a decision tree regressor, and a random forest regressor, may be used to estimate the number of bikes at a certain station. The owners of bike sharing systems may efficiently redistribute their bikes and plan ahead with the support of accurate bike count projections, guaranteeing that all users have easy access to the available bikes. Overall, this study seeks to solve some of green IoT’s related difficulties while highlighting the advantages and its possible uses in the bike sharing system. © 2024 selection and editorial matter, Neha Sharma, Jai Prakash Verma, Sunil Gautam, Valentina Emilia Balas, and Saravanan Krishnan; individual chapters, the contributors.
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