Smart Parking: An Efficient System for Parking and Payment

In addition to being a time-consuming and annoying driving experience, searching for a cheap and empty parking space also wastes fuel and pollutes the air. In densely populated cities, there are limited and expensive public parking spaces. On the other hand, private parking spaces are typically underutilized, and the parking space owners are willing to charge higher parking fees to cover the expenses of maintaining their excess parking capacity. In light of these circumstances, it is essential to look for a smart parking system that gathers and allows private parking spaces to ease the worries of public parking. An Internet of Things (IoT) enabled parking space recommendation system is proposed in this paper. It makes recommendations by utilizing IoT technology (traffic and parking sensors). The recommended system helps users automatically pick a spot at the lowest charge by accounting for metrics like distance, availability of vacancy at the slot, and the charges. To accomplish this, the user parking cost is calculated using performance measures. This system provides the user with a way to request a parking spot when one is available, as well as a way to recommend a new parking lot if the present one is filled. The proposed model reduces user waiting time and increases the likelihood of finding an empty slot in the parking, based on the simulation results used besides offering an anonymous payment method. The proposed system also exploited the concept of VANET as it uses onboard and roadside units. The novelty of the research is that apart from calculating the cost function it also maintains the neighbors table at each neighbor which will be shared among all as and when there is a change. We have simulated the environment in Network Simulator 3 (NS3).

@article{Ahmed2024,
  title     = {Smart Parking: An Efficient System for Parking and Payment},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {6},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Md Ezaz Ahmed and Mohammad Arif and Mohammad Khalid Imam Rahmani and Md Tabrez Nafis and Javed Ali},
  doi       = {10.14569/IJACSA.2024.01506130},
  url       = {https://doi.org/10.14569/IJACSA.2024.01506130}
}