Design Of Deep Learning Model Applied For Smart Parking System

Abstract

This article proposes and introduces a smart parking system using RFID technology incorporating a Deep Learning model to identify license plates. It tries to simulate the ability of the brain to recognize, differ- entiate and learn patterns from data. The employed algorithms are mainly based on neural network mod- els where neurons are organized in stacked layers. The system is designed to manage incoming and outgoing vehicles by collecting and processing images and data on passenger information to update parking status with the news of empty lots. Another function of the park- ing system also designed is a fully automatic method of paying the parking fee by the user. The deep learning model for the smart parking system is implemented us- ing the Raspberry PI 3 embedded system and sensors. Experimental results with the plate identification rate in the worst condition, up to 80%, have proven the re- liability of the proposed smart parking system. In terms of quantity, the percentage of the worst plate identifi- cation down to 10% has established the stability of the proposed smart parking system.