{"title":"Parking Space Occupancy Monitoring System Using Computer Vision and IoT","authors":"Luiz Eduardo Giampaoli, Fabiano Hessel","doi":"10.1109/WF-IoT51360.2021.9595935","DOIUrl":null,"url":null,"abstract":"The process of organizing and managing parking spaces presents challenges for both the public and private sectors. Many of these challenges are caused by the inability to generate new parking spaces at the same pace as population adherence to new vehicles. Constantly improving technology in the fields of sensing and machine vision allow us to create systems that offer functionalities that are impractical to be performed with low human resources in large parking operations. An example of this type of functionality is real-time parking space occupancy monitoring. The objective of this work is the development of a system to monitor the occupancy of parking spaces. To achieve this goal, computer vision related technology integrated by an IoT platform will be used. The system was validated using different scenarios with different lighting intensities. The results are very promising even in cases where there was low ambient light","PeriodicalId":184138,"journal":{"name":"2021 IEEE 7th World Forum on Internet of Things (WF-IoT)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 7th World Forum on Internet of Things (WF-IoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WF-IoT51360.2021.9595935","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The process of organizing and managing parking spaces presents challenges for both the public and private sectors. Many of these challenges are caused by the inability to generate new parking spaces at the same pace as population adherence to new vehicles. Constantly improving technology in the fields of sensing and machine vision allow us to create systems that offer functionalities that are impractical to be performed with low human resources in large parking operations. An example of this type of functionality is real-time parking space occupancy monitoring. The objective of this work is the development of a system to monitor the occupancy of parking spaces. To achieve this goal, computer vision related technology integrated by an IoT platform will be used. The system was validated using different scenarios with different lighting intensities. The results are very promising even in cases where there was low ambient light