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A Review on Smart IOT Based Parking System

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Recent Advances on Soft Computing and Data Mining (SCDM 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 978))

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Abstract

With the rapid proliferation in population of the big cities, numbers of vehicles are also growing with proportionate pace. People prefer to use private transport rather than public transport which results an increase in the number of vehicles. Thus, finding vacant parking place becomes cumbersome, resulting in several issues like increase in consumption of fuel, time and energy. Thanks to the Internet of things (IOT) that has advanced so much and opened a new spectrum of technologies that were previously considered as science fiction. Almost every field is inclined to get benefits from IOT. Big cities or metropolitan cities are also on the track of smart cities by exploiting IOT and addressing issues such as traffic congestion, limited car parking facilities and road safety. In this paper, we have reviewed some research papers from the recent work carried out in the year 2018 to 2019 related to IOT based smart parking. In their investigations different models augmented with sensors, integrating cloud and mobile application are presented, which subsequently yields in a smart parking system which saves time, energy, fuel and subsequently carbon footprint. It is noticed that disabled people are ignored to be addressed in their systems and there is no single global parking solution exists so far. The rapid development in miniaturization and robustness of processors, sensor and coupling with machine learning added to the potential of smart and single global solution feasible for future researchers to address parking issues exists in both indoor and outdoor parking lots.

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Correspondence to Adil Ali Saleem .

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Saleem, A.A., Siddiqui, H.U.R., Shafique, R., Haider, A., Ali, M. (2020). A Review on Smart IOT Based Parking System. In: Ghazali, R., Nawi, N., Deris, M., Abawajy, J. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2020. Advances in Intelligent Systems and Computing, vol 978. Springer, Cham. https://doi.org/10.1007/978-3-030-36056-6_26

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