Ruzelita Ngadiran
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Ruzelita Ngadiran
Official Name
Ruzelita, Ngadiran
Alternative Name
Ngadiran, Ruzelita
Ngadiran, R.
Binti Ngadiran, Ruzelita
Main Affiliation
Scopus Author ID
36548898800
Researcher ID
ABF-3045-2020

Research Output

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  • Publication
    IOT Smart Guidance Parking Search System for Open Space Parking Area
    ( 2021-07-26)
    Iszaidy Ismail
    ;
    Ruzelita Ngadiran
    ;
    Nazren A.R.A.
    ;
    Wafi N.M.
    ;
    Ramli N.
    ;
    Vijayasarveswari Veeraperumal
    ;
    Leow W.Z.
    Open parking facilities can be automated and parking spaces can be easily operated by the implementation of IoT technology (Internet of Things). In this article, we present the evolution and prototyping of the open space smart guidance-parking search system, an IoT-based smart parking search system. The Smart Guidance Parking Searches System consists of i) An IOT module to monitor the availability of a parking slot and to update the parking lot status; and (ii) A web-based software allows users to view parking spaces available for a specific open space area. This paper addresses the existing system, device description, its functional specifications, the methods, and technologies used, the development/deployment of prototypes, along with the findings from the demonstration. This device serves as a guide for the user/driver to search for the parking slot occupancy in open/outdoor environments.
  • Publication
    An Analysis of Background Subtraction on Embedded Platform Based on Synthetic Dataset
    ( 2021-03-01)
    Iszaidy Ismail
    ;
    Ruzelita Ngadiran
    ;
    R Badlishah Ahmad
    ;
    Ramli N.
    ;
    Jais M.I.
    ;
    Vijayasarveswari Veeraperumal
    Background subtraction is a preliminary technique used for video surveillance and a widely used approach for indexing moving objects. Arange of algorithms have been introduced over the years, and it might be hard to implement the algorithms on the embedded platform because the embedded platform comes up with limited processing power. The goal of this study is to provide a comparative analysis of available background subtraction algorithms on the embedded platform:-Raspberry Pi. The algorithms are compared based on the segmentation quality (precision, recall, and f-measure) and hardware performance(CPU usage and time consumption) using a synthetic video from BMC Dataset with different challenges like normal weather, sunny, cloudy, foggy and windy weather.
  • Publication
    Background Subtraction Algorithm Comparison on the Raspberry Pi Platform for Real Video Datasets
    ( 2022-01-01)
    Iszaidy Ismail
    ;
    Ruzelita Ngadiran
    ;
    Ramli N.
    ;
    Nazren A.R.A.
    ;
    Nasruddin M.W.
    ;
    Jais M.I.
    Background subtraction is an advanced method used for video monitoring and is commonly used for indexing of moveable objects. Over the years, several algorithms have been implemented and the implementation of algorithms on the embedded platform can be difficult because the embedded platform has minimal computing resources. The purpose of this study is to conduct a comparative review of background subtraction algorithms available on the embedded platform: Raspberry Pi. The algorithms are compared using a real video dataset based on segmentation accuracy (precision, recall, and f-measure) and hardware efficiency (CPU utilization and time consumption).