Abstract
The automated car parking system is a system which helps the people to park their vehicles without any confusion in a mall or hospital or theatre or any parking layout. This automated car parking system takes the footage of the parking layout which is given as input and is made standard for the model. It is used to find empty and filled parking slots. Then with that information, it directs the user or the person who comes inside the parking to the empty slot or gives a message that the parking is full. The system is trained using Deep learning with different images of parking slots with empty cars and parking slots with the car filled. The objective is to leverage the CNN Deep Learning model for Smart Parking. The main problem in car parking is the improper management of land resources, which leads to a great shortage in parking space causing chaos in our daily lives. Parking is one of the biggest challenges that we need to tackle in the years to come. Using smart parking, there is proper utilization of the parking space and makes the experience pleasant.
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We would thank Impiger Technologies Pvt. Ltd for their support and help throughout our project.
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Appendix 1
Appendix 1
See Figs. 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 and 19.
Loading the dataset
Summary of a model
Training the model
Model accuracy
Model loss
Proper classification
Improper classification
Grayscale conversion
Determining the edges of grayscale conversion
Region of interest
Determination of outline of parking slots
Determination of parking lanes
Final layout of slots and lanes
Figure of the final output
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Karpagam, G.R., Ganapathy, A., Kavin Raj, A.C., Manigandan, S., Neeraj Julian, J.R., Raaja Vignesh, S. (2021). Leveraging CNN Deep Learning Model for Smart Parking. In: Ahmed, K.R., Hassanien, A.E. (eds) Deep Learning and Big Data for Intelligent Transportation. Studies in Computational Intelligence, vol 945. Springer, Cham. https://doi.org/10.1007/978-3-030-65661-4_8
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