Autonomous Parking Spot Detection System for Mobile Phones using Drones and Deep Learning

Show simple item record
dc.contributor.authorTirado, Guilleum Budia
dc.contributor.authorSemwal, Sudhanshu
dc.contributor.editorSkala, Václav
dc.date.accessioned2021-08-31T08:53:44Z
dc.date.available2021-08-31T08:53:44Z
dc.date.issued2021
dc.description.abstract-translatedMany parking lot facilities suffer from capacity over-loads and many times there are no monitoring tools toprovide feedback. As a consequence, the people, want-ing to park, become frustrated as there is considerablyloss of time. In this paper, we present a novel proto-type of an automatic parking-lot analysis platform us-ing image-based machine learning to (a) guide a droneautonomously; and (b) to process useful information tobe handled into a smartphone application to communi-cate with the parking lot users.We have collected a reasonable amount of test imagesto build a classification model using Convolutional neu-ronal networks (CNNs) to classify parking lot images,and build different object detection models to identifyfree and occupied parking spots. Those models havebeen exported to the back-end module of our platformso it can control the drone and record the computed in-formation to its database. In addition, we have imple-mented an iOS application that requests and displaysthe parking lot status and its empty spots.We have been able to prove that this prototype is fea-sible, functional, and opens a path towards future im-provements and refinements. The flight control and thedata classification algorithms have been shown to workusing the machine learning models. In summary, wefound a clear and and concise way to display useful in-formation in real time to our users.en
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationWSCG 2021: full papers proceedings: 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 115-124.en
dc.identifier.doihttps://doi.org/10.24132/CSRN.2021.3101.13
dc.identifier.isbn978-80-86943-34-3
dc.identifier.issn2464-4617
dc.identifier.issn2464–4625(CD/DVD)
dc.identifier.urihttp://hdl.handle.net/11025/45016
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.rights© Václav Skala - UNION Agencycs
dc.rights.accessopenAccessen
dc.subjectdronycs
dc.subjectARcs
dc.subjectparkovištěcs
dc.subjectnavigacecs
dc.subjecthluboké učenícs
dc.subject.translateddronesen
dc.subject.translatedARen
dc.subject.translatedparking loten
dc.subject.translatednavigationen
dc.subject.translateddeep learningen
dc.titleAutonomous Parking Spot Detection System for Mobile Phones using Drones and Deep Learningen
dc.typeconferenceObjecten
dc.typekonferenční příspěvekcs
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

Files

Original bundle
Showing 1 - 1 out of 1 results
No Thumbnail Available
Name:
I19.pdf
Size:
11.8 MB
Format:
Adobe Portable Document Format
Description:
Plný text
Download
License bundle
Showing 1 - 1 out of 1 results
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

WSCG 2021: Full Papers Proceedings