IoT Based Smart Parking System Using Deep Long Short Memory Network
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 create...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-10-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/9/10/1696 |
| _version_ | 1797550828635029504 |
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| author | Ghulam Ali Tariq Ali Muhammad Irfan Umar Draz Muhammad Sohail Adam Glowacz Maciej Sulowicz Ryszard Mielnik Zaid Bin Faheem Claudia Martis |
| author_facet | Ghulam Ali Tariq Ali Muhammad Irfan Umar Draz Muhammad Sohail Adam Glowacz Maciej Sulowicz Ryszard Mielnik Zaid Bin Faheem Claudia Martis |
| author_sort | Ghulam Ali |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T15:35:59Z |
| format | Article |
| id | doaj.art-ef65cdd224e645f8bd8cca5637e93b54 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T15:35:59Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-ef65cdd224e645f8bd8cca5637e93b542023-11-20T17:16:48ZengMDPI AGElectronics2079-92922020-10-01910169610.3390/electronics9101696IoT Based Smart Parking System Using Deep Long Short Memory NetworkGhulam Ali0Tariq Ali1Muhammad Irfan2Umar Draz3Muhammad Sohail4Adam Glowacz5Maciej Sulowicz6Ryszard Mielnik7Zaid Bin Faheem8Claudia Martis9Department of Computer Science, University of Okara, Okara 56130, PakistanDepartment of Computer Science, COMSATS University Islamabad, Sahiwal Campus, Sahiwal 57000, PakistanCollege of Engineering, Electrical Engineering Department, Najran University, Najran 61441, Saudi ArabiaComputer Science Department, University of Sahiwal, Sahiwal 57000, PakistanDepartment of Computer Science, University of Okara, Okara 56130, PakistanAutomatics, 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, PolandFaculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24 Str., 31-155 Cracow, PolandFaculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24 Str., 31-155 Cracow, PolandComputer Science Department, University of Engineering and Technology, Taxila, Punjab 47080, PakistanFaculty of Electrical Engineering, Technical University of Cluj-Napoca, Str. Memorandumuluinr. 28, 400114 Cluj-Napoca, RomaniaTraffic 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.https://www.mdpi.com/2079-9292/9/10/1696internet of thingsdeep long short term memory (LSTM)car parkingsmart citysmart parkingdeep learning |
| spellingShingle | Ghulam Ali Tariq Ali Muhammad Irfan Umar Draz Muhammad Sohail Adam Glowacz Maciej Sulowicz Ryszard Mielnik Zaid Bin Faheem Claudia Martis IoT Based Smart Parking System Using Deep Long Short Memory Network Electronics internet of things deep long short term memory (LSTM) car parking smart city smart parking deep learning |
| title | IoT Based Smart Parking System Using Deep Long Short Memory Network |
| title_full | IoT Based Smart Parking System Using Deep Long Short Memory Network |
| title_fullStr | IoT Based Smart Parking System Using Deep Long Short Memory Network |
| title_full_unstemmed | IoT Based Smart Parking System Using Deep Long Short Memory Network |
| title_short | IoT Based Smart Parking System Using Deep Long Short Memory Network |
| title_sort | iot based smart parking system using deep long short memory network |
| topic | internet of things deep long short term memory (LSTM) car parking smart city smart parking deep learning |
| url | https://www.mdpi.com/2079-9292/9/10/1696 |
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