Latifah Mohamed
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Preferred name
Latifah Mohamed
Official Name
Mohamed , Latifah
Alternative Name
Mohamed, Latifah
Mohamed, L.
Main Affiliation
Scopus Author ID
16943523200
Researcher ID
IAK-5403-2023

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  • Publication
    Simulation of Radio Tomographic Imaging for Measurement Rice Moisture Content
    ( 2020-08-01)
    Mohammed Saeed Moqbel Abdullah
    ;
    Latifah Munirah Kamarudin
    ;
    Mohd Hafiz Fazalul Rahiman
    ;
    Latifah Mohamed
    ;
    Ammar Zakaria
    Radio Tomographic Imaging (RTI) is an emerging technology for imaging the attenuation caused by physical objects in wireless networks that perform wireless receive signal strength (RSS) measurements obtain a reconstruction of objects inside an area of interest to know the different moisture content of rice in the silo. The simulation results analysis has been performed. The image of the phantoms was reconstructed by the selected image reconstruction algorithms, which are Linear Back Projection (LBP), Filtered Back Projection (FBP), and Gaussian. Evaluation of this work was assessed by using three image quality assessment techniques Mean Structural Similarity Index (MSSIM). MSSIM was used to analyze the reconstructed images. Among the three proposed images reconstruction algorithms linear back projection, filtered back projection, and Gaussian algorithm. Gaussian seems to be a more reliable option for reconstructing the image of moisture content of rice in a silo by using 20 RF nodes in the RTI system. This paper discusses in detail the use of shadowing losses on links between RF sensors in a wireless community to image the attenuation of moisture content inside the wi-fi network vicinity.
      1
  • Publication
    Simulation of Radio Tomographic Imaging for Measurement Rice Moisture Content
    ( 2020-08-01)
    Abdullah M.S.M.
    ;
    Latifah Munirah Kamarudin
    ;
    Mohd Hafiz Fazalul Rahiman
    ;
    Latifah Mohamed
    ;
    Ammar Zakaria
    Radio Tomographic Imaging (RTI) is an emerging technology for imaging the attenuation caused by physical objects in wireless networks that perform wireless receive signal strength (RSS) measurements obtain a reconstruction of objects inside an area of interest to know the different moisture content of rice in the silo. The simulation results analysis has been performed. The image of the phantoms was reconstructed by the selected image reconstruction algorithms, which are Linear Back Projection (LBP), Filtered Back Projection (FBP), and Gaussian. Evaluation of this work was assessed by using three image quality assessment techniques Mean Structural Similarity Index (MSSIM). MSSIM was used to analyze the reconstructed images. Among the three proposed images reconstruction algorithms linear back projection, filtered back projection, and Gaussian algorithm. Gaussian seems to be a more reliable option for reconstructing the image of moisture content of rice in a silo by using 20 RF nodes in the RTI system. This paper discusses in detail the use of shadowing losses on links between RF sensors in a wireless community to image the attenuation of moisture content inside the wi-fi network vicinity.
      1