Detecting Available Parking Spaces in Smart Cities

The concept of smart cities is realizing between vehicles, road networks, smart parking, smart mobility, smart environment, living, and people coupled with human population growth and needs. Therefore, the smart city has evolved over time, and improved the quality of human life using technologies. This paper proposes a fine-tuned model based on Mask-RCNN to implement and test “available parking spaces in smart cities”. The fine-tuned model performed well in classification accuracy. It demonstrates good performance and practical value in smart cities. Smart city is fast motivating to making technological solution for achieving smart mobility (transportation systems) more intelligent. This motivation takes us to compile new trends of AI and deep learning on the different aspects of smart city. Therefore, this paper presents an effort that can be taken up as research work for smart parking. Our result shows that; the proposed work outperforms in the detection of smart parking.