IoT based smart parking system using deep long short memory network
Authors:
- Ghulam Ali,
- Tariq Ali,
- Muhammad Irfan,
- Umar Draz,
- Muhammad Sohail,
- Adam Glowacz,
- Maciej Sulowicz,
- Ryszard Mielnik,
- Zaid Bin Faheem,
- Claudia Martis
Abstract
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.
- Record ID
- CUT33565f4dfe7145e4b95b6276a970faab
- Publication categories
- ;
- Author
- Journal series
- Electronics (Switzerland), ISSN , e-ISSN 2079-9292, Bimonthly
- Issue year
- 2020
- Vol
- 9
- No
- 10
- Pages
- [1-17]
- Article number
- 1696
- Other elements of collation
- schem.; tab.; wykr.; Bibliografia (na s.) - 16-17; Bibliografia (liczba pozycji) - 33; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 9, Iss. 10
- Substantive notes
- Section: Networks
- Keywords in English
- internet of things, deep long short term memory (LSTM), car parking, smart city, smart parking, deep learning
- DOI
- DOI:10.3390/electronics9101696 Opening in a new tab
- URL
- https://www.mdpi.com/2079-9292/9/10/1696/htm Opening in a new tab
- Related project
- E-mobilność oraz zrównoważone materiały i technologie. . Project leader at PK: , ,
- Language
- eng (en) English
- License
- Score (nominal)
- 100
- Publication indicators
- Citation count
- 82
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT33565f4dfe7145e4b95b6276a970faab/
- URN
urn:pkr-prod:CUT33565f4dfe7145e4b95b6276a970faab
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.