Machine Learning based Vacant Space Detection for Smart Parking Solutions

Urban areas of countries around the world are plagued with parking space shortages, because of the burgeoning population of private vehicles. Lack of information on parking space availability for drivers causes the drivers to waste time searching for an off-street parking space, thereby contributing...

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Bibliographic Details
Published in2023 International Conference on Control, Communication and Computing (ICCC) pp. 1 - 6
Main Authors Francis, Shalu, Ouseph, Anjana, S, Durgaprasad, Abdulla, Hani, Lal, Akhil, Likhith, S., K J, Dhanaraj, M, Harikrishna
Format Conference Proceeding
LanguageEnglish
Published IEEE 19.05.2023
Subjects
Cameras
Image processing
Machine Learning
Machine learning algorithms
Object Detection
Smart Parking
Sociology
Space vehicles
Surveillance
Urban areas
Wireless communication
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Summary:Urban areas of countries around the world are plagued with parking space shortages, because of the burgeoning population of private vehicles. Lack of information on parking space availability for drivers causes the drivers to waste time searching for an off-street parking space, thereby contributing to traffic congestion. With surveillance cameras being used for security purposes, the images captured from the same can be conveniently used for the detection of vacant parking slots. This paper proposes a machine learning-based vacant space detection of vacant parking spaces. The 'YOLO' algorithm is used to identify the occupied parking slots by processing the images obtained from the surveillance cameras, from which the positions of vacant parking slots are derived. The output from the implementation of the YOLO algorithm is used to estimate vacant parking slots using the proposed algorithms. The proposed system is found to give very accurate estimates of the vacant slots for demarcated and non-demarcated parking lots.
DOI:10.1109/ICCC57789.2023.10165557