Extreme Learning Machine for Parking Slot Recognition in Smart Parking System

In the modern era, technology has become an integral part of human life, particularly in image processing. This advanced technology is now applied to parking areas to identify vacant parking spaces. The application is designed to detect empty parking slots in real time using image data captured by a camera as input. The system then automatically scans for available parking spaces, displaying the results on the interface with green indicators for empty slots and red for occupied ones. The process involves several key stages, such as image pre-processing, image segmentation, and object detection. The system employs the Extreme Learning Machine (ELM) method to enhance its object detection capabilities. This system achieves a high accuracy rate of 94%under well-lit conditions. This novel technology optimizes parking management, providing an effective and dependable method to monitor parking availability in real time.

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Publication Details

Published
2024-11-21
DOI
https://doi.org/10.1109/elticom64085.2024.10865423
Primary Topic
Smart Parking Systems Research
Type
article
Field-Weighted Citation Impact
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article

Extreme Learning Machine for Parking Slot Recognition in Smart Parking System

Romi Fadillah Rahmat, Mohd Amiruddin Abd Rahman, Sharfina Faza, Pauzi Ibrahim Nainggolan et al.
Smart Parking Systems Research
article

Extreme Learning Machine for Parking Slot Recognition in Smart Parking System

Romi Fadillah Rahmat, Mohd Amiruddin Abd Rahman, Sharfina Faza, Pauzi Ibrahim Nainggolan, Riza Sulaiman, Irwanda Syahputra
article en

Abstract

In the modern era, technology has become an integral part of human life, particularly in image processing. This advanced technology is now applied to parking areas to identify vacant parking spaces. The application is designed to detect empty parking slots in real time using image data captured by a camera as input. The system then automatically scans for available parking spaces, displaying the results on the interface with green indicators for empty slots and red for occupied ones. The process involves several key stages, such as image pre-processing, image segmentation, and object detection. The system employs the Extreme Learning Machine (ELM) method to enhance its object detection capabilities. This system achieves a high accuracy rate of 94%under well-lit conditions. This novel technology optimizes parking management, providing an effective and dependable method to monitor parking availability in real time.

Universiti Putra Malaysia (MY), State University of Medan (ID), Universitas Sumatera Utara (ID), National University of Malaysia (MY)
Sustainable cities and communities
Openalex Percentile: Top 71%
Smart Parking Systems Research
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