Ku Nurul Fazira Ku Azir
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Preferred name
Ku Nurul Fazira Ku Azir
Official Name
Ku Azir, Ku Nurul Fazira
Alternative Name
Ku Azir, Ku Nurul Fazira
Fazira Ku Azir, Ku Nurul
Azir, Ku
Azir, Ku Nurul Fazira Ku
Azir, K. N.F.K.
Ku Azir, K. N.F.
Azir, K. N.F.Ku
Main Affiliation
Scopus Author ID
56879016500
Researcher ID
AAY-3466-2021

Research Output

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  • Publication
    LaundryMama: Humanising Laundry Tasks using Laundry Management System and Laundry-On-Demand Mobile Applications
    ( 2020-03-20)
    Mei L.Y.
    ;
    Ku Nurul Fazira Ku Azir
    ;
    Siti Zuraidah Ibrahim
    ;
    Saidatul Norlyana Azemi
    Laundry Management System and Laundry-On-Demand Mobile Applications are presented in this paper. Using conventional laundry service method, customer is not informed about the laundry process stage, does not have option to arrange the preferred laundry pick up time for the deliveryman to pick up the unwashed laundry from the address provided by customer and the laundry ordering paper forms are often lost in transit between customer and admin. Therefore, a laundry management system software and laundry on demand mobile application is demanded to solve the problems. The software development is performed using an open source developing platform Android Studio IDE and Firebase Real-time Database, Authentication, Cloud Messaging and Cloud Storage. The method used to develop the software is waterfall modelling and two characters are involved, which is admin and customer. The two characters functions are separated in two different applications. A Laundry Management System Software is developed for admin to manage, make order and monitor the business. A Laundry-On-Demand Mobile Application is developed for customer to make order and monitor the order. These both applications can receive notification from each other. The data can be correctly written and read from Firebase Real-time database, Firebase Authentication, Firebase Cloud Storage. The developed software and mobile application are evaluated in term of its functionality.
  • Publication
    A general framework for improving electrocardiography monitoring system with machine learning
    ( 2019-03-01)
    Khairuddin A.M.
    ;
    Ku Nurul Fazira Ku Azir
    ;
    Eh Kan P.
    As one of the most important health monitoring systems, electrocardiography (ECG) is used to obtain information about the structure and functions of the human heart for detecting and preventing cardiovascular disease. Given its important role, it is vital that the ECG monitoring system provides relevant and accurate information about the heart. Over the years, numerous attempts were made to design and develop more effective ECG monitoring system. Nonetheless, the literature reveals not only several limitations in conventional ECG monitoring system but also emphasizes on the need to adopt new technology such as machine learning to improve the monitoring system as well as its medical applications. This paper reviews previous works on machine learning to explain its key features, capabilities as well as presents a general framework for improving ECG monitoring system.
  • Publication
    R-Peaks and Wavelet-Based Feature Extraction on K-Nearest Neighbor for ECG Arrhythmia Classification
    ( 2024-01-01)
    Khairuddin A.M.
    ;
    Ku Nurul Fazira Ku Azir
    ;
    Mohd Rashidi Che Beson
    The aim of this research is to classify 17 types of arrhythmias by applying the algorithm developed from combining the morphological and the wavelet-based statistical features. The proposed arrhythmia classification algorithm consists of four stages: pre-processing, detection of R-peaks, feature extraction, and classification. Seven morphological features (MF) that were retrieved from the R-peak locations. Following this, another nine wavelet-based statistical features (SF) were gathered by decomposing wavelets in level 4 from the Daubechies 1 wavelet (Db1). These 16 features are then applied to the k-nearest neighbor (k-NN) algorithm. The accuracy (ACC) of the suggested classification algorithm was assessed by using the MIT-BIH arrhythmia benchmark database (MIT-BIHADB). The experimental results of this work attained an average accuracy (ACC) of 99.00%.
  • Publication
    Performance and Stamina Wearable Devices and Monitoring System for Football Players
    ( 2023-10-06)
    Kamarudzaman M.F.
    ;
    Ku Nurul Fazira Ku Azir
    ;
    Siti Zuraidah Ibrahim
    ;
    Ujir H.
    Analysing and monitoring the performance of football players is not something new in the world of football. Having to analyse and monitor the player’s performance, the coaching staff and manager can see the player’s development and at the same time the training drills can be more effective. There are three main player’s attributes that coaching staff and manager need to monitor, which are speed, acceleration, and stamina. The system available today does not represent the player’s performance for each of the attributes in terms of values. This project is aiming to design and develop a system that can analyse and monitor the football player’s performance using micro-electronic technology (MEM) like accelerometer and gyroscope. There will be two microcontrollers that are responsible for controlling the interaction between other components and uploading the collated data into cloud storage. This project will use the ThingSpeak platform to generate the player’s development graph. This platform is available in the form of websites and smartphone applications. By implementing IoT into the system, the coaching staff and manager can monitor the player’s development anywhere at any time. The system is successfully read and analysed the player’s attributes performance for speed, acceleration, and stamina in form of values and graphs where at the same time the project is also capable of analysing the player’s penalty kick technique.
  • Publication
    Ambient Cues of Kitchen Counter in Guiding Cooking Activities for Alzheimer's Patient
    ( 2019-03-01)
    Basharudin N.W.
    ;
    Ku Nurul Fazira Ku Azir
    ;
    Khairuddin A.M.
    ;
    Ehkan P.
    Loss of memory is among the first symptoms reported by patients suffering from Alzheimer's disease (AD). The individual pattern of impaired memory functions correlates with functional brain integrity will result in the inability of the patient to complete a particular task. This research focuses on designing the ambient cues in the kitchen counter to guide Alzheimer's patient to complete cooking activities based on the concept of Stimulus-Response Compatibility (SRC) and whereas the activity is focus on the sequential workflow of cooking activities based on the Hierarchical Task Analysis (HTA). Wizard-of-Oz is used to simulate the behavior of theoretical intelligent ambient cues. The results show with the aid of ambient cues in the kitchen, patient be able to complete the task until the end even if there is confusing or disruption in the middle of the activity. The effectiveness of ambient cues show that patient can easily understood the cues of guiding the cooking flow when mistakes happened.
  • Publication
    IoT-based Door Access Using Three Security-Layers
    ( 2023-10-06)
    Aznan M.A.
    ;
    Siti Zuraidah Ibrahim
    ;
    Ku Nurul Fazira Ku Azir
    ;
    Ruzelita Ngadiran
    ;
    Mohd Noh F.H.
    This paper demonstrates an Internet-of-Things, IoT-based Door Access using three security layers, which are biometric identification, authentication, and authorized reply. The IoT-based door access is developed with Closed Circuit Television (CCTV) monitoring to control door access by authorized users using facial recognition technique and the Telegram application along with a database to record user logs. In the first security layer, the user’s face will be captured by CCTV camera and then processed to match to the registered face. In the authentication layer, the system will use Telegram Bot to send a message to the user registered Telegram Chat Identification (ID) only for entering the password. In the third security layer, if the password is valid, the system will send a signal to the hardware to unlock the door. The results showed that the developed prototype of this system successfully operated as expected.
  • Publication
    Techniques for Developing QRS Enhancement and Detection Algorithms in Electrocardiography (ECG): A Review
    ( 2024-05-10)
    Khairuddin A.M.
    ;
    Ku Nurul Fazira Ku Azir
    ;
    Mohd Rashidi Che Beson
    Algorithms are increasingly being used and recognized for their ability to improve the performance of diagnostic tools such as contemporary electrocardiogram (ECG). For instance, evidence from previous studies reveals that QRS enhancement and detection algorithms have enabled the ECG device to measure and classify heartbeat more accurately. Based on the review of the previous works on QRS detection in ECG, this paper examines the key components of the ECG, QRS detection features, the different techniques used for developing QRS enhancement and detection algorithms as well as the criteria for evaluating their performance.