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A New Framework for Smart Doors Using mmWave Radar and Camera-Based Face Detection and Recognition Techniques.
Akbari, Younes; Al-Binali, Abdulaziz; Al-Mohannadi, Ali; Al-Hemaidi, Nawaf; Elharrouss, Omar; Al-Maadeed, Somaya.
Afiliación
  • Akbari Y; Department of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, Qatar.
  • Al-Binali A; Department of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, Qatar.
  • Al-Mohannadi A; Department of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, Qatar.
  • Al-Hemaidi N; Department of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, Qatar.
  • Elharrouss O; Department of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, Qatar.
  • Al-Maadeed S; Department of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, Qatar.
Sensors (Basel) ; 24(1)2023 Dec 28.
Article en En | MEDLINE | ID: mdl-38203032
ABSTRACT
By integrating IoT technology, smart door locks can provide greater convenience, security, and remote access. This paper presents a novel framework for smart doors that combines face detection and recognition techniques based on mmWave radar and camera sensors. The proposed framework aims to improve the accuracy and some security aspects arising from some limitations of the camera, such as overlapping and lighting conditions. By integrating mmWave radar and camera-based face detection and recognition algorithms, the system can accurately detect and identify people approaching the door, providing seamless and secure access. This framework includes four key components person detection based on mmWave radar, camera preparation and integration, person identification, and door lock control. The experiments show that the framework can be useful for a smart home.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Qatar Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Qatar Pais de publicación: Suiza