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Proximity-Based Optical Camera Communication with Multiple Transmitters Using Deep Learning.
Nasution, Muhammad Rangga Aziz; Herfandi, Herfandi; Sitanggang, Ones Sanjerico; Nguyen, Huy; Jang, Yeong Min.
Afiliación
  • Nasution MRA; Department of Electronics Engineering, Kookmin University, Seoul 02707, Republic of Korea.
  • Herfandi H; Department of Electronics Engineering, Kookmin University, Seoul 02707, Republic of Korea.
  • Sitanggang OS; Department of Electronics Engineering, Kookmin University, Seoul 02707, Republic of Korea.
  • Nguyen H; Department of Electronics Engineering, Kookmin University, Seoul 02707, Republic of Korea.
  • Jang YM; Department of Electronics Engineering, Kookmin University, Seoul 02707, Republic of Korea.
Sensors (Basel) ; 24(2)2024 Jan 22.
Article en En | MEDLINE | ID: mdl-38276392
ABSTRACT
In recent years, optical camera communication (OCC) has garnered attention as a research focus. OCC uses optical light to transmit data by scattering the light in various directions. Although this can be advantageous with multiple transmitter scenarios, there are situations in which only a single transmitter is permitted to communicate. Therefore, this method is proposed to fulfill the latter requirement using 2D object size to calculate the proximity of the objects through an AI object detection model. This approach enables prioritization among transmitters based on the transmitter proximity to the receiver for communication, facilitating alternating communication with multiple transmitters. The image processing employed when receiving the signals from transmitters enables communication to be performed without the need to modify the camera parameters. During the implementation, the distance between the transmitter and receiver varied between 1.0 and 5.0 m, and the system demonstrated a maximum data rate of 3.945 kbps with a minimum BER of 4.2×10-3. Additionally, the system achieved high accuracy from the refined YOLOv8 detection algorithm, reaching 0.98 mAP at a 0.50 IoU.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article Pais de publicación: Suiza