LabVIEW Based Automated Parking System

The Automated Parking System (APS) initiative uses cutting-edge technology to solve typical parking-related issues in small and medium-sized businesses, thereby improving urban mobility and efficiency. The goal of this project is to create and deploy an automated system with servo motors, ultrasonic sensors, Arduino-based microcontrollers, and an intuitive online interface. The principal objective is to optimize the procedure for identifying and scheduling parking spots, consequently mitigating traffic and enhancing customer comfort. The APS sends real-time data to a central database by using ultrasonic sensors to determine if each parking space is occupied. Users can then log in, reserve parking spaces, and get a special access code using this data via a web interface. Drivers enter their access code at the entrance keypad upon arrival, causing the system to validate the code and, if it is valid, open the associated barriers. Due to the system's dynamic updating of slot availability, users are always given update with correct information. The APS's functionality and real-time data processing capabilities are demonstrated through the integration of a basic simulation using MATLAB and LabVIEW, underscoring the system's potential to greatly enhance parking management. Notwithstanding obstacles like preserving security and guaranteeing sensor accuracy under diverse circumstances, the APS offers a scalable, reasonably priced solution designed for smaller parking lots. This study lays the groundwork for next advancements in automated parking technologies, which will hopefully increase accessibility to and benefit from sophisticated parking assistance for a larger variety of enterprise.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/nigercon62786.2024.10927346
Citations
1
Primary Topic
Industrial Automation and Control Systems
Type
article
Field-Weighted Citation Impact
0.33
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article

LabVIEW Based Automated Parking System

M. J. E. Salami, Jogun-Omi Fawaz Olatunbosun
1 citations
Industrial Automation and Control Systems
0.33
article

LabVIEW Based Automated Parking System

M. J. E. Salami, Jogun-Omi Fawaz Olatunbosun
article en
1 citations

Abstract

The Automated Parking System (APS) initiative uses cutting-edge technology to solve typical parking-related issues in small and medium-sized businesses, thereby improving urban mobility and efficiency. The goal of this project is to create and deploy an automated system with servo motors, ultrasonic sensors, Arduino-based microcontrollers, and an intuitive online interface. The principal objective is to optimize the procedure for identifying and scheduling parking spots, consequently mitigating traffic and enhancing customer comfort. The APS sends real-time data to a central database by using ultrasonic sensors to determine if each parking space is occupied. Users can then log in, reserve parking spaces, and get a special access code using this data via a web interface. Drivers enter their access code at the entrance keypad upon arrival, causing the system to validate the code and, if it is valid, open the associated barriers. Due to the system's dynamic updating of slot availability, users are always given update with correct information. The APS's functionality and real-time data processing capabilities are demonstrated through the integration of a basic simulation using MATLAB and LabVIEW, underscoring the system's potential to greatly enhance parking management. Notwithstanding obstacles like preserving security and guaranteeing sensor accuracy under diverse circumstances, the APS offers a scalable, reasonably priced solution designed for smaller parking lots. This study lays the groundwork for next advancements in automated parking technologies, which will hopefully increase accessibility to and benefit from sophisticated parking assistance for a larger variety of enterprise.

Afe Babalola University (NG)
Openalex Percentile: Top 36%
Industrial Automation and Control Systems
0.33
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LabVIEW Based Automated Parking System — M. J. E. Salami, Jogun-Omi Fawaz Olatunbosun · (2024) | TGRS Research Map | TGRS