Abstract
Various research works in computer science utilize data generated from cities, to make it smart and intelligent. Some of these works make use of data mining, sensor networks, internet of things, web of things, cloud computing techniques and machine learning techniques. In this work, smart mobility using data mining is mainly focused upon. Smart mobility is one of the crucial aspects of smart city addressing efficient movement of people and goods from one place to another. In the present work, several literature works on smart mobility have been discussed along with suggested improvement in mobility for several locations in India. This work focuses upon the issue of reduction in visibility in environment, which is caused by presence of certain atmospheric conditions. Reduction in visibility hinders traffic and causes accidents, thus affecting smooth movement of people and goods. The present work examines the humidity content of several locations in India, specifically metropolitan city of Bangalore have been considered in this research. Furthermore, clustering have been performed to investigate the humidity trends at these locations and results are found to be promising.
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Aggarwal, A., Toshniwal, D. (2018). Visibility Prediction in Urban Localities Using Clustering. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 906. Springer, Singapore. https://doi.org/10.1007/978-981-13-1813-9_37
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DOI: https://doi.org/10.1007/978-981-13-1813-9_37
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