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Open AccessArticle

IoT Based Smart Parking System Using Deep Long Short Memory Network

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Department of Computer Science, University of Okara, Okara 56130, Pakistan
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Department of Computer Science, COMSATS University Islamabad, Sahiwal Campus, Sahiwal 57000, Pakistan
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College of Engineering, Electrical Engineering Department, Najran University, Najran 61441, Saudi Arabia
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Computer Science Department, University of Sahiwal, Sahiwal 57000, Pakistan
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Automatics, Computer Science and Biomedical Engineering, Department of Automatic Control and Robotics, Faculty of Electrical Engineering, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Kraków, Poland
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Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24 Str., 31-155 Cracow, Poland
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Computer Science Department, University of Engineering and Technology, Taxila, Punjab 47080, Pakistan
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Faculty of Electrical Engineering, Technical University of Cluj-Napoca, Str. Memorandumuluinr. 28, 400114 Cluj-Napoca, Romania
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Authors to whom correspondence should be addressed.
Electronics 2020, 9(10), 1696; https://doi.org/10.3390/electronics9101696
Received: 12 September 2020 / Revised: 6 October 2020 / Accepted: 13 October 2020 / Published: 15 October 2020
(This article belongs to the Section Networks)
Traffic congestion is one of the most notable urban transport problems, as it causes high energy consumption and air pollution. Unavailability of free parking spaces is one of the major reasons for traffic jams. Congestion and parking are interrelated because searching for a free parking spot creates additional delays and increase local circulation. In the center of large cities, 10% of the traffic circulation is due to cruising, as drivers nearly spend 20 min searching for free parking space. Therefore, it is necessary to develop a parking space availability prediction system that can inform the drivers in advance about the location-wise, day-wise, and hour-wise occupancy of parking lots. In this paper, we proposed a framework based on a deep long short term memory network to predict the availability of parking space with the integration of Internet of Things (IoT), cloud technology, and sensor networks. We use the Birmingham parking sensors dataset to evaluate the performance of deep long short term memory networks. Three types of experiments are performed to predict the availability of free parking space which is based on location, days of a week, and working hours of a day. The experimental results show that the proposed model outperforms the state-of-the-art prediction models. View Full-Text
Keywords: internet of things; deep long short term memory (LSTM); car parking; smart city; smart parking; deep learning internet of things; deep long short term memory (LSTM); car parking; smart city; smart parking; deep learning
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MDPI and ACS Style

Ali, G.; Ali, T.; Irfan, M.; Draz, U.; Sohail, M.; Glowacz, A.; Sulowicz, M.; Mielnik, R.; Faheem, Z.B.; Martis, C. IoT Based Smart Parking System Using Deep Long Short Memory Network. Electronics 2020, 9, 1696.

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