Mohd Ilman Jais
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Preferred name
Mohd Ilman Jais
Official Name
Mohd Ilman , Jais
Alternative Name
Jais, Mohd I.
Jais, M. I.
Jais, Mohd Ilman
Main Affiliation
Scopus Author ID
17434740200
Researcher ID
AAY-6716-2021

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  • Publication
    Video size comparison for embedded vehicle speed detection & travel time estimation system by using Raspberry Pi
    ( 2017-03-06)
    Iszaidy Ismail
    ;
    Alias A.
    ;
    Ruzelita Ngadiran
    ;
    R Badlishah Ahmad
    ;
    Mohd Ilman Jais
    ;
    Shuhaizar Daud
    As traffic continues to grow up, the issue regarding the road accident also growing quickly. The accident occurred due to the high speed of vehicles on the road. This paper proposed a vehicle speed detection and travel time estimation system using Raspberry Pi to estimate the speed of passing vehicles through this system. The system is designed to detect the moving vehicles and calculate its velocity. The system used OpenCV as an image processing software to detect and track the moving vehicles. Several types of capturing size of the video are used in this system to check and measure the performance of the embedded board.
      3  56
  • Publication
    Threading implementation on different hardware for travel time estimation purpose
    ( 2017-03-06)
    Iszaidy Ismail
    ;
    Ruzelita Ngadiran
    ;
    R Badlishah Ahmad
    ;
    Mohd Ilman Jais
    ;
    Shuhaizar Daud
    The travel time estimation is one of traffic management system which provide time taken from one point to another point. Travel time estimation system consists of an embedded platform with image sensor for detecting and tracking the vehicle. Due to limited resources of embedded board, it makes challenging to measure the travel time especially for fast moving vehicle. Capturing system required a high capturing rate of the camera to capture most current frame for fast moving vehicle. Threading is implemented in this system to improve embedded board resource utilization and input-output latency between camera and embedded board. In this paper, the threading technology is applied to two types of Raspberry Pi model and the performance of the embedded board is recorded and analyzed.
      56  16
  • Publication
    A school attendance management system by using facemask recognition based on the internet of things (IoT) approach
    ( 2024-02-08)
    Amir Nazren Abdul Rahim
    ;
    Muhammad Syakir Shafie
    ;
    Abdullah W.A.N.W.
    ;
    Mohd Ilman Jais
    ;
    Iszaidy Ismail
    ;
    Mohd Wafi Nasrudin
    ;
    Che Muhammad Nor Che Isa
    This project focuses primarily on developing a student attendance management system using a Raspberry Pi machine with Deep Learning and Computer Vision technologies. The main objective of this project is to assist school authorities who are struggling to maintain student attendance, especially during this global pandemic of COVID-19. This is done by implementing technology of facemask recognition, Quick Response (QR) code as data identification, temperature detection, storing the data in the database, and lastly, user monitoring. In addition, students can protect themselves from Covid-19 disease using this method based on the Standard Operating Procedure (SOP) implementation. The initial stage of this system is recognizing whether the students wear masks properly or not. Then, the QR code is scanned to provide the identity of the students and the data is saved. The Raspberry Pi is programmed to continuously monitor students at the school entrance. The board is set up to collect temperature data from the K3 Pro device and eventually uploaded the data to the Google Sheet database together with QR code identity data. Later, the data can be viewed through an android smartphone and the system can be controlled by the school authorities in charge. Every single process of this system is run and updated based on real-time data recording.
      4
  • Publication
    Rpi as a mechanism to control reconfigurable receiver ability of RSSI scanning and tracking system modeling
    ( 2024-02-08)
    Mohd Ilman Jais
    ;
    Mohd Wafi Nasrudin
    ;
    Che Muhammad Nor Che Isa
    ;
    Amir Nazren Abdul Rahim
    ;
    Iszaidy Ismail
    This paper presents a scanning and tracking system based on received signal strength indication (RSSI). Deployed raspberry-pi (Rpi) is used as a mechanism to control reconfigurable receiver ability and as a tracking decision maker based on captured incoming RSSI. The proposed prototype is verified by the obtained real-time experimental and found as ±4° and angle error for mode II and III of reconfigurable receiver. Hence, this work validates Rpi as a mechanism to control reconfigurable receiver ability of RSSI scanning and tracking system modeling with minimum angle error.