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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1001
DC FieldValueLanguage
dc.contributor.authorDo Anh Tuanen_US
dc.date.accessioned2021-03-09T03:33:59Z-
dc.date.accessioned2021-03-09T03:34:03Z-
dc.date.available2021-03-09T03:33:59Z-
dc.date.available2021-03-09T03:34:03Z-
dc.date.issued2020-
dc.identifier.urihttp://epub.vgu.edu.vn/handle/dlibvgu/1001-
dc.description.abstractThis thesis introduces an alternative solution using a deep learning method along with advanced technologies. The Raspberry Pi is responsible for handling the camera’s inputs and sending them to a local server. MobileNet-Single Shot Detector model is a suitable approach in human detection because it achieves the balance between the speed and the accuracy. The system only detects people’s presence, not their identities. The workflow of the system is simple. The system detects humans in the frames, records a video, and uploads it to a cloud storage. Users will be notified whenever there are any humans in the supervised area with a picture of them. However, users can not remotely interact with the system. The proposed solution is operational but still needs more improvement to fulfill the real-world requirements.-
dc.language.isoen-
dc.publisherVietnamese-German University-
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectHome surveillance-
dc.subjectDeep learning-
dc.subjectInternet of things-
dc.subjectRaspberry Pi-
dc.titleDesign and analysis of a camera surveillance system in a house by using Raspberry Pi-
dc.typeThesis-
item.grantfulltextrestricted-
item.fulltextWith Fulltext-
item.languageiso639-1other-
Appears in Collections:Computer Science (CS)
Computer Science (CS)
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