Mohd Firdaus Ibrahim
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Preferred name
Mohd Firdaus Ibrahim
Official Name
Mohd Firdaus , Ibrahim
Alternative Name
Ibrahim, M. F.
Ibrahim, Mohd Firdaus
Main Affiliation
Scopus Author ID
56571962400
Researcher ID
AAE-5507-2020

Research Output

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  • Publication
    Smart Gateless System using RFID Technology in Universiti Malaysia Perlis
    ( 2021-06-11)
    Ainur Fasihah Mohd Fazilah
    ;
    Muzammil Jusoh
    ;
    Ammar Zakaria
    ;
    Thennarasan Sabapathy
    ;
    Mohd Firdaus Ibrahim
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Muhammad Mokhzaini Azizan
    ;
    Mohd Zakimi Zakaria
    ;
    Nashrul Fazli Mohd Nasir
    ;
    Albreem M.A.M.
    ;
    R Badlishah Ahmad
    This paper describes a smart monitoring gate-less system by using RFID technologies that had been implemented in Universiti Malaysia Perlis. The objective of this system is to ease the security to monitoring the cars-in and cars-out from the main gate manually. The security can check and manage the staff by system management in PC. This smart monitoring gate-less system consists of RFID tag antenna that be attached at sticker's staff, RFID reader and software management application. For the software management application, this project used LabView as a simulation tool for the data acquisition. The data which contains of name, staff number, number plate, car model and color will be stored in cloud-based storage. All the information data can be accessed from any location because the security management can access it through mobile. This project will present how efficient the vehicle control application on campus which enable the security guard to check a car sticker either legal or illegal in a shortest way.
      1
  • Publication
    Design of Compact UHF-RFID Tag Antenna with Meander Line Technique
    ( 2020-03-20)
    Fazilah A.F.M.
    ;
    Muzammil Jusoh
    ;
    Ammar Zakaria
    ;
    Thennarasan Sabapathy
    ;
    Mohd Firdaus Ibrahim
    ;
    Mohamed Nasrun Osman
    ;
    Yaasin M.N.
    ;
    Malhotra S.
    ;
    Hasliza A Rahim @ Samsuddin
    In this paper, a compact UHF RFID tag antenna that can operate at Malaysia UHF RFID frequency (860 MHz - 960MHz) is proposed. The antenna with a common geometry structure without any shorting pin consists of 90degree angled line (meander line) and double T-match structure. The proposed antenna has been designed and simulated using CST Simulation software. The proposed tag antenna design shows a good performance in terms of size, gain and impedance with a dimension of 36 mm 25 mm 1.6 mm. The simulated gain of antenna obtained is -0.135 dB at 910 MHz with 19 MHz bandwidth.
      1
  • Publication
    In-Line sorting of Harumanis Mango based on external quality using visible imaging
    ( 2016)
    Mohd Firdaus Ibrahim
    ;
    Fathinul Syahir Ahmad Sa'ad
    ;
    Ammar Zakaria
    ;
    Ali Yeon Md Shakaff
    The conventional method of grading Harumanis mango is time-consuming, costly and affected by human bias. In this research, an in-line system was developed to classify Harumanis mango using computer vision. The system was able to identify the irregularity of mango shape and its estimated mass. A group of images of mangoes of different size and shape was used as database set. Some important features such as length, height, centroid and parameter were extracted from each image. Fourier descriptor and size-shape parameters were used to describe the mango shape while the disk method was used to estimate the mass of the mango. Four features have been selected by stepwise discriminant analysis which was effective in sorting regular and misshapen mango. The volume from water displacement method was compared with the volume estimated by image processing using paired t-test and Bland-Altman method. The result between both measurements was not significantly different (P > 0.05). The average correct classification for shape classification was 98% for a training set composed of 180 mangoes. The data was validated with another testing set consist of 140 mangoes which have the success rate of 92%. The same set was used for evaluating the performance of mass estimation. The average success rate of the classification for grading based on its mass was 94%. The results indicate that the in-line sorting system using machine vision has a great potential in automatic fruit sorting according to its shape and mass.
      4  11