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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 8, 2020.
Abstract: Cloud computing with an amalgamation of the internet of things (IoT) typically gave birth to an ideal field called Cloud of things (CoT). CoT maintains revolutionary services in every domain, but it has instantly become a rising star in smart transportation because a well-organized facility might present a challenge for dealing with the exponentially expanding people living in smart cities. Lack of management in transport can cause distress among people and nowadays parking has come to be one of the critical issues faced by the public daily. In this paper, we present a parking availability prediction model implemented within a geo-fence ranging from 100-150 meters based on cloud, IoT, and GIS. In contrast to present models, instead of offering no space or parking is full; our model accurately determines the ETA of a vehicle and checks the potential/chance of parking availability. It also calculates the time for the next parking space if the existing parking space accessibility is zero. Moreover, our model includes all the exogenous factors like weather, time zone conditions to gain prediction accuracy.
Nazish Razzaq, Muhammad Asaad Subih, Madiha Khatoon, Amir Razi, Babur Hayat Malik, Nimra Ashraf, Tehseen Kausar, Rashida Tarrar, Muhammad Usman Sabir and Syed Izaz ul Hassan Bukhari, “Cloud of Things (CoT) based Parking Prediction” International Journal of Advanced Computer Science and Applications(IJACSA), 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110879
@article{Razzaq2020,
title = {Cloud of Things (CoT) based Parking Prediction},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110879},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110879},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {8},
author = {Nazish Razzaq and Muhammad Asaad Subih and Madiha Khatoon and Amir Razi and Babur Hayat Malik and Nimra Ashraf and Tehseen Kausar and Rashida Tarrar and Muhammad Usman Sabir and Syed Izaz ul Hassan Bukhari}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.