Abstract

In Internet of Things (IOT)-based smart cities, negative reasons such as cost, energy and air pollution when searching for a parking space increase the importance of smart parking systems. In this study, a two-stage hybrid approach is proposed so that drivers can find a parking space that will consume the least time and energy. The first stage focuses on car parks having at least one free parking space located near the target address in an n diameter circumference, which are also open for business. An AVL tree-based hierarchical structure is created with driving time from the starting point to each car park and walking time from each car park to the destination, and it focuses on the most appropriate car park. In the second stage, the most suitable parking space is searched and made available, if found, in hierarchical parking monitoring system. In order to demonstrate the effectiveness of the approach, the results compared with hierarchical, hierarchical Binary Search Tree (BST) and non-hierarchical solutions in terms of energy and time performance are shown on a simulation. Proposed approach gave the best result with 99% energy efficiency. In addition, a dynamic cloud-based reservation system was proposed for the parking lot determined in the study.

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