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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Rouabah, Boubakeur | - |
dc.contributor.author | Cheikha, Aya Ilham | - |
dc.contributor.author | Acila, Hani | - |
dc.date.accessioned | 2024-09-18T10:20:03Z | - |
dc.date.available | 2024-09-18T10:20:03Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | FACULTE DES NOUVELLES TECHNOLOGIES DE L'INFORMATIQUE ET DE LA COMMUNICATION | en_US |
dc.identifier.uri | https://dspace.univ-ouargla.dz/jspui/handle/123456789/36742 | - |
dc.description.abstract | In non-main etrances to the house , many people use surveillance cameras and security systems to avoid theft ;but the latter may incluse some issues in the detection process and the high cost , this is what prompte us to search for a device that includes solutions to the previous problems montioned This thesis presents the development and implimentation of a home security system using Raspberry Pi and deep learning techniques ; this system benefits from its low costs and high accuracy in the detection process | en_US |
dc.language.iso | en | en_US |
dc.publisher | UNIVERSITY KASDI MERBAH OUARGLA | en_US |
dc.subject | security system | en_US |
dc.subject | smart home | en_US |
dc.subject | cost | en_US |
dc.subject | deep learning | en_US |
dc.subject | Rasberry P | en_US |
dc.title | Smart Home security system using Raspberry Pi and YOLOv8 | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Département d'Electronique et des Télécommunications - Master |
Files in This Item:
File | Description | Size | Format | |
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CHEIKHA-ACILA.pdf | 3,03 MB | Adobe PDF | View/Open |
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