Muhamad Khairul Ali Hassan
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Preferred name
Muhamad Khairul Ali Hassan
Official Name
Muhamad Khairul , Ali Hassan
Alternative Name
Hassan, Muhamad Khairul Ali
Hassan, M. K.Ali
Khairul Ali Hassan, Muhamad
Hassan, M. K.A.
Ali Hassan, M. K.
Main Affiliation
Scopus Author ID
55537856900
Researcher ID
GSD-4118-2022

Research Output

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A Device-to-Device (D2D) Communication between Mobile Robots using Wireless Communication Protocol in Dynamic Environments

2024-03-11 , Sarhan M.A.H. , Hashim M.S.M. , Abdul Halim Ismail , Mohd Nasir Ayob , Hassrizal Hassan Basri , Muhamad Safwan Muhamad Azmi , Othman S.M. , Kanafiah S.N.A.M. , Muhamad Khairul Ali Hassan

Mobile robots must have the ability to guarantee safety for operation in a dynamic environment and close to other moving objects. There are many research had been conducted to make the robot safer by utilizing sensors and big data technology to make the mobile robot able to navigate autonomously and intelligently. One of the key elements in autonomous robots is communication between robots. In this paper, device-to-device (D2D) technology has been used to develop communication between robots. To establish the algorithm for D2D communications, radio frequency (RF) used as communication protocols that can perform D2D communication in real-time applications. The performance of D2D communication was then be assessed in terms of distance and latency. RF transceiver module has been mounted on the robot with Arduino to allow communication between mobile robot to other mobile robots in order to transfer data from robot's sensors to the other mobile robots. By utilizing the gathered information and data, the robot can assess its surroundings and predict the movement of other robots to avoid collisions between robots. The results show that the RF transceiver module is capable to send and receive data between two robots with latency up to 4.865s. It is envisaged that the proposed module can be very useful for developing D2D communication between robots to operate in dynamic environments.

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Aquaculture monitoring system using multi-layer perceptron neural network and adaptive neuro fuzzy inference system

2024-01-01 , Abu Hassan Abdullah , Sukhairi Sudin , Saad F.S.A. , Muhamad Khairul Ali Hassan , Muhammad Imran Ahmad , bin Abdul Khalid K.A.

The water quality is the most important parameter for aquatic species health and growth. The condition is very critical and is essential to monitor continuously. Poor water quality will affect health, growth and ability of the animal to survive. These also affected their harvesting yields based on the amount and size of the animal. The main water parameters such dissolved oxygen (DO), pH, temperature, salinity and turbidity are monitored and control for good water quality. The data were acquired by the developed instrument and send wirelessly through GPRS/GSM module to cloud-based database. The data were retrieved and the water quality is predicted using fuzzy logic and multi-layer perceptron. MATLAB software was used for the model which is developed based on Mamdani fuzzy interface system. The membership functions of fuzzy were generated, as well as the simulation and analysis of the water quality system. Results show that the performance of fuzzy method can improve system performance in monitoring the water quality. This system also provides alert signals to farmers based on specific limit value for the water quality parameters. This will help the breeders to make certain adjustment to ensure suitable water quality for the aquaculture system.

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An IoT Agricultural System for Harumanis Farm

2021-12-01 , Ismail F.A. , Muhamad Khairul Ali Hassan , Fathinul Syahir Ahmad Sa'ad , Haniza Yazid , Muhammad Juhairi Aziz Safar , Khairul Salleh Basaruddin , Abdul Halim Ismail , Mohd Nasir Ayob

Internet of Things (IoT) is a revolutionary technology that represents the future of communication and computing. The field of IoT implementation is vast and can be applied in every field. This project is about to develop an IoT system for Harumanis Farm as agriculture is becoming an essential growing sector throughout the world due to the increasing population. The major challenge in the Harumanis sector is to improve the productivity and quality of Harumanis without continuous manual monitoring. IoT improves crop management, cost-effectiveness, crop monitoring and also improves the quality and quantity of the crop. This IoT system completes with several sensors to monitor the Harumanis farm, such as temperature and humidity sensor, pH level sensor, soil moisture sensor, also nitrogen, phosphorous, and potassium (NPK) sensor. The system is a simple IoT architecture where sensors collect information and send it over the Wi-Fi network to the mobile applications.

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Pre- and Post-operative Assessment of Bone with Osteogenesis Imperfecta using Finite Element Analysis: A Review

2024-02-01 , Wanna Soh Bua Chai , Khairul Salleh Basaruddin , Mohd Hanafi Mat Som , Fauziah Che Mat , Muhamad Khairul Ali Hassan

Applications of finite element analysis (FEA) to demonstrate the pre-and post-operative conditions of the brittle bone-related disease known as osteogenesis imperfecta (OI) has been widely used in the past and at present. The method used to reconstruct the bone model that resemble the OI bone geometry plays an important aspect to accurately represent the bone condition to provide more alternative ways to evaluate surgical intervention options. Other factors such as material properties and boundary conditions also reflect the results of the analysis. Therefore, the aim of this review paper is to analyse the approaches of previous studies in terms of model geometry construction, selection of materials properties and boundary conditions to enable a deeper understanding and evaluation of bone fractures in OI patients. The biomechanical design of the intramedullary (IM) rods used in post-operative surgery and the interface between IM rods and bone fragments are also discussed in this review paper.

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Analysis on Clustering Based Method for Diabetic Retinopathy Using Color Information

2022-01-01 , Selvam S.A , Haniza Yazid , Shafriza Nisha Basah , Fathinul Syahir Ahmad Sa'ad , Muhamad Khairul Ali Hassan

Diabetic Retinopathy (DR) is an important global health concern and it can causes blindness. Early detection and treatment can prevent the patients from loss their vision. This study presents an approach of color image segmentation for automatic exudate detection. The color retinal images are converted into four different color spaces and preprocessed by applying Contrast Limited Adaptive Histogram Equalization (CLAHE). Fuzzy C-Means (FCM) and K-means clustering (KMC) algorithms are applied on the preprocessed image for the segmentation purpose. Then, optic disc is detected and eliminated by using Circular Hough Transform (CHT). Performance evaluation of developed algorithm is done using Structured Analysis of the Retina (STARE) dataset. The proposed algorithm achieved sensitivity of 93.4% for STARE datasets for LUV color space with KMC.

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Design of a portable continuous systolic blood pressure monitoring kit with built-in low and high blood pressure early warnings

2009 , Muhamad Khairul Ali Hassan

About one in three adults in the United States have high blood pressure but high blood pressure itself usually has no symptoms. The prevalence of hypertension in Malaysians aged 30 years and above was 42.6%. The majority of cases (64%) in this country remain undiagnosed. Only 26% of Malaysian patients achieved blood pressure control (<140/90 mmHg). Now days, many people have high blood pressure for years without knowing it. Uncontrolled high blood pressure can lead to stroke, heart attack, heart failure or kidney failure. This is why high blood pressure is often called the "silent killer." The only way to tell if you have high blood pressure is to have your blood pressure checked. Blood pressure is often measured using a device called a sphygmomanometer, a stethoscope and a blood pressure cuff. Almost all the existing manual or automatic measuring techniques of blood pressure are based on this principle, which is not convenient for continuous monitoring of blood pressure. The objective of this study is to develop a portable continuous blood pressure monitoring system using an electrocardiography (ECG) sensor and a pulse sensor. Two methods were used to measure blood pressure continuously. The first method measures blood pressure continuously based on Heart Rate (HR) and the second method is based on Pulse Wave Transit Time (PWTT). Both methods were separately implemented for different techniques to measure systolic blood pressure (SBP). The techniques that were used to model the relationship between the PWTT or HR data to systolic blood pressure are linear regression model, non- linear regression model and neural network model. Neural network model gave the smallest value of mean of error and standard deviation of error for measuring blood pressure based on PWTT or HR. These errors are acceptable and relatively small compared to the standard accuracy, which should have a minimum mean of error value of 6 mmHg with a standard deviation of error of ±10mmHg. The subjects that were involved in portable BP monitoring kit testing are normal blood pressure subjects, low blood pressure subjects and high blood pressure subjects. All the data were taken about five minutes for each subject and the results were monitored by medical cardiologist/doctor or nurses. The accuracy of the SBP data from portable continuous BP monitoring kit was validated using sphygmomanometer. The results indicate that the developed portable BP system is adequate to be used for monitoring or measuring systolic blood pressure continuously. Warning system was developed in this portable BP monitoring kit. The warning system is generated based on blood pressure value and trend of increasing or decreasing of systolic blood pressure values. The warning is given in form of alarm. The alarm will be “on” when the systolic blood pressure value goes more than 140mmHg (High Blood Pressure) or less than 100mmHg (Low Blood Pressure) or if the SBP increasing or decreasing trend in more than 5mmHg for each 30 seconds.

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Effect of Image Thresholding on the Homogenized Properties of Trabecular Bone Model

2022-01-01 , Khairul Salleh Basaruddin , Haniza Yazid , Muhammad Juhairi Aziz Safar , Mohd Hafif Basha Mohamad Jamel Basha , Fathinul Syahir Ahmad Sa'ad , Muhamad Khairul Ali Hassan

This paper presents a numerical study to determine the homogenized (apparent) properties of vertebral trabecular bone with different threshold values using homogenization method. Series set of micro-CT images of vertebral trabecular bone was used in the present digital image-based modeling technique to reconstruct the microstructure model. Three image thresholding values were selected based on Otsu’s method. The homogenized properties that include the Young’s moduli, Poisson’s ratio and shear moduli was obtained in this study. The results showed there is significant effect of image threshold on the homogenized properties of vertebral trabecular bone model.

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Potential of Near-Infrared (NIR) spectroscopy technique for early detection of Insidious Fruit Rot (IFR) disease in Harumanis mango

2021-12-01 , Noor Shazliza Zakaria , Abu Hassan Abdullah , Fathinul Syahir Ahmad Sa'ad , Muhamad Khairul Ali Hassan , Mohd Nazri Abu Bakar , Saad A.R.M. , Sukhairi Sudin , Ibrahim M.F.

Harumanis mango 'Insidious Fruit Rot'(IFR), is one of the common issues that hampered the fruit quality and consequently lowered the premium value of Harumanis Mango. Physically and visually the affected fruit does not show any attributes that indicates the presence of IFR on any part of the fruit until it has been cut open. This paper investigates the feasibility of a non-destructive method to screen the Harumanis mango from IFR using near-infra red light and artificial neural network. A common NIR light emitting diodes of 1000nm wavelength was used as the light source to emit NIR light while a photodiode was used to measure the intensity of the reflected NIR light from Harumanis mango. Early detection of IFR were done manually by local expert using acoustic method by flicking fingers to detect any abnormality inside the fruit. Sample data on NIR Spectroscopy reflectance results of 120 samples were used to classify the presence of IFR using neural network. Mean value of NIR reflectance of RBG for Harumanis mango with an incidence of Insidious Fruit Rot are R= 0.651, G= 0.465 and B=0.458, while without IFR are R = 0.211, G=0.15 and B=0.146. Using MATLAB's neural network training tool, a training set regression was obtained with an accuracy value of 0.9805 for prediction of IFR, thus this value is very high in accuracy.

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Development of a Common Waste Combustion System for Generating Electricity at Remote Area

2023-01-01 , Zaini A.S.A. , Sukhairi Sudin , Haris F.A. , Nurul Syahirah Khalid , Fathinul Syahir Ahmad Sa'ad , Muhamad Khairul Ali Hassan , Ibrahim I.I.

Malaysia's daily amount of municipal solid waste (MSW) has rapidly increased. This causes the landfills number to increase due to inadequate waste management systems. Apart from that, Malaysia depends on non-renewable resources for electricity generation which could have a significant effect on the environment. Therefore, this study proposed to reduce landfills in Malaysia in a proper way and supply electricity using municipal solid waste as a renewable resource. In this study, the combustion of municipal solid waste (MSW) produces steam, which will rotate a turbine that is connected to a dynamo. Then, the energized dynamo will supply electricity to appliances including a direct current motor. The motor shaft then rotates the dynamo shaft in the pulley system which causes the electricity to flow in a closed loop. In this system, a pressurized container is crucial to produce sufficient steam. Based on the experimental setup, it was observed that continuous electricity was successfully achieved by looping the system using a pulley on the dynamo and motor.

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Single Channel Magnetic Induction Measurement for Meningitis Detection

2021-01-01 , Aiman Abdulrahman Ahmed , Zulkarnay Zakaria , Ali M.H. , Pusppanathan J. , Rahim R.A. , Muji S.Z.M. , Anas Mohd Noor , Mohd Hafiz Fazalul Rahiman , Muhamad Khairul Ali Hassan , Muhammad Juhairi Aziz Safar , Ahmad Faizal Salleh

Bacterial meningitis is one of the most common and prominent infections which infects the central nervous system through the tissue layers and membranes that cover our brain and spinal cord. It is a staggering and fatal illness that kills patients within hours. The number of meningitis cases that has been recorded annually around the world are one million cases and 135,000 deaths. Early detection and start of sufficient treatment are considered as the main determinants for better result. MIT mechanism is noncontact electrodes of impedance measurement. This mechanism uses induction principle instead of contact electrodes to get the required information. This paper presents an overview on the potential of Magnetic induction tomography (MIT) in detecting meningitis disease. In MIT principle, single channel measurement process which consist of transmitter (Tx) and receiver (Rx) coil has been studied. In this field is disclosed about passive electrical field (PEP) which focuses on the three parameters which are dielectric permittivity, electrical conductivity, and magnetic permeability. In addition, this research project involves experimental setup. The applied frequency is between 1–10 MHz. Finally, in this project, the performance of the square coil with 12 number of turns (5Tx–12Rx) with 10 MHz frequency has been identified as the suitable transmitter-receiver pair and the optimum frequency for detecting the conductivity property distribution of brain tissues.

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