Wan Mohd Faizal Wan Nik
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Wan Mohd Faizal Wan Nik
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Wan Mohd Faizal, Wan Nik
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Physical, electrical and optical characterizations of Ba0.5Sr0.5TiO3 (BST) thin films

2020-01-08 , Bakar Nurhanani Abu , Adnan Johari , Rozana Aina Maulat Osman , Zul Azhar Zahid Jamal , Muhammad Asri Idris , Wan Mohd Faizal Wan Nik , Man Bahari

Single layer Barium Strontium Titanate (BaxSr1-xTiO3) thin films were deposited on P type Silicon (Si) and thin Silicon Dioxide (SiO2) layer grown on Silicon (Si) substrate (1.5 cm x 1.5 cm) using spin coating technique were investigated in this work. The thin films were crystallized by annealing at 950 °C for 4 hours. Physical characterization was performed using XRD. Electrical and optical characterizations were aided by depositing Aluminum (Al) using Physical Vapor Deposition (PVD) on the thin films as electrode metal. I-V profile was obtained using Semiconductor Parametric Analyzer (SPA). A high impedance multimeter, light meter and a variable light source were introduced for optical characterizations including optical sensitivity, current density and I-V profile under variable light intensity from 0 to 900 Lux. Results show BST has diode like characteristics. The results which were compared with those from commercial solar cells and light sensors indicated that the BST thin films have potential as solar power generator and sensor.

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Turbulent Kinetic Energy of Flow during Inhale and Exhale to Characterize the Severity of Obstructive Sleep Apnea Patient

2023-01-01 , Wan Mohd Faizal Wan Nik , Khor Chu Yee , Yaakob M.N.C. , Ghazali N.N.N. , Zainon M.Z. , Ibrahim N.B. , Razi R.M.

This paper aims to investigate and present the numerical investigation of airflow characteristics using Turbulent Kinetic Energy (TKE) to characterize the upper airway with obstructive sleep apnea (OSA) under inhale and exhale breathing conditions. The importance of TKE under both breathing conditions is that it show an accurate method in expressing the severity of flow in sleep disorder. Computational fluid dynamics simulate the upper airway’s airflow via steady-state Reynolds-averaged Navier-Stokes (RANS) with k–ω shear stress transport (SST) turbulence model. The three-dimensional (3D) airway model is created based on the CT scan images of an actual patient, meshed with 1.29 million elements using Materialise Interactive Medical Image Control System (MIMICS) and ANSYS software, respectively. High TKE were noticed around the region after the necking (smaller cross-sectional area) during the inhale and exhale breathing. The turbulent kinetic energy could be used as a valuable measure to identify the severity of OSA. This study is expected to provide a better understanding and clear visualization of the airflow characteristics during the inhale and exhale breathing in the upper airway of patients for medical practitioners in the OSA research field.

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Computational fluid dynamic study of the pharyngeal airway characteristics before and after mandibular setback surgery in patients with mandibular prognathism

2022-03-01 , Aqilah N. , Wan Mohd Faizal Wan Nik , Khor Chu Yee , Ghazali N.N.N. , Zainon M.Z. , Ismail M.A.

Mandibular prognathism had been one of the most inconvenienced deformities developed in humans. This type of deformity possesses a protruded mandible jaw, and it can cause inconvenience in talking chewing and affect the aesthetic of the person diagnosed with this problem. However, this problem can be solved through mandibular setback surgery. This surgery will reposition the mandible jaw backward. The main concern of this surgery is, by repositioning the mandible jaw backward, the cross-sectional area of the airway will also be reduced. This condition might induce the iatrogenic of Obstructive Sleep Apnea (OSA). Thus, this study analyzed the characteristic of the pharyngeal airway in pre-treatment and post-virtual-operative conditions. This analysis simulates the pharyngeal airway with the Computational Fluid Dynamic (CFD) method. The respondent's data was obtained from computed tomography (CT) scan and was modeled into a 3-dimensional (3D) model. The simulation process takes place using the 3D model, mesh generation, and boundary conditions set-up. The flow pattern, pressure drop, airway wall shear stress, and turbulent kinetic energy were compared between both simulations. The simulations result present that, after the surgery, the pharyngeal airway decreases significantly. The pressure drop, flow pattern, airway wall shear stress (WSS), and turbulent kinetic energy (TKE) seem more significant around the critical plane in the post-treatment condition. However, these factors did not contribute to the OSA as it is not large enough to become the cause of OSA.

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IoT Enabled Mushroom Farm Automation with Machine Learning

2024-06-03 , Shafie Omar , Wan Mohd Faizal Wan Nik , Muhammad Imran Ahmad , Tan Shie Chow , Mohd Nazri Abu Bakar , Shahrul Fazly Man@Sulaiman , Fadhilnor Abdullah , Vikneshwara Ram Suppiah

Mushroom farming has gained prominence due to its significant contribution to the global market. One major challenge for mushroom cultivation is maintaining optimal environmental conditions, specifically temperature and humidity. Traditional farming methods, prevalent in many parts of the world, lack precise control over these parameters, often leading to poor yield. This paper presents an innovative approach combining the Internet of Things (IoT) and Machine Learning (ML) for mushroom farm automation. The proposed system employs the ESP8266 microcontroller with specific agricultural sensors for smart monitoring. To regulate the farm's environmental conditions, ML algorithms predict mushroom farm weather states: mild, normal, and hot. The ensemble ML model, comprising five classifiers – Decision Tree, Logistic Regression, K-nearest neighbor, Support Vector Machine, and Random Forest – delivers a commendable accuracy of 100% when combining predictions, surpassing the performance of individual classifiers. This integrated IoT and ML approach promises to revolutionize real-time automation and cultivation practices in the mushroom industry.

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Plant Disease Classification Using Image Processing Technique

2024-06-03 , Shahrul Fazly Man@Sulaiman , Shafie Omar , Muhammad Imran Ahmad , Wan Mohd Faizal Wan Nik , Tan Shie Chow , Mohd Nazri Abu Bakar , Fadhilnor Abdullah , Asbhir Yuusuf Omar

Agriculture remains pivotal to our economy, with farming playing a central role in revenue generation. Challenges such as pests, plant diseases, and evolving climate patterns pose threats to crop yield and production. Addressing these challenges, timely and accurate detection of plant diseases emerges as imperative. Manual detection, however, remains resource-intensive and often lags. Addressing this gap, this project proposes an innovative image processing-based system for rapidly detecting plant diseases. The system proficiently identifies specific diseases by analyzing images of plant leaves against a curated dataset. The emphasis of this study was on three major diseases: Bacterial Blight (with an accuracy of 98.6%), Alternaria Alternata (98.5714%), and Cercospora Leaf Spot (97.5%). The compelling results underline the system's capacity to swiftly and effectively categorize diseases, offering monoculture farmers an indispensable tool for obtaining prompt, disease-specific insights.

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Intelligent irrigation system using rain water harvesting system and fuzzy interface system

2021-12 , Azremi Abdullah Al-Hadi , Sukhairi Sudin , Ahmad Z.A , Fathinul Syahir Ahmad Sa'ad , I Ahmad , Fadhilnor Abdullah , Wan Mohd Faizal Wan Nik , A. Deraman , N. M Maliki , S R S Kamaruzaman , S R Romle

Shortage of water has become a predominant problem all over the world as water plays an important role in agriculture, domestic and industry. In certain parts of the world, farmers face problems watering their crops especially during the dry season. Limited water resources with low efficiency greatly affect crop growth. Therefore, this study proposes an intelligent irrigation system using Rain Water Harvesting (RWH) and Fuzzy Interface System (FIS) for crops watering process. The RWH is a system that collects, centralises and stores rainwater, while the FIS uses temperature and soil moisture sensors to determine the time and amount needed for the watering process. Thus, the intelligent irrigation system will ensure the process of watering the crops to be efficient. The results of this study show that FIS can analyse temperature and soil moisture data, which improves the efficiency of crops watering process and the use of RWH will make it sustainable. The developed project is currently operating at the Institute of Sustainable Agro Technology, i.e. a university-owned agricultural research institute.

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AI Assisted and IOT Based Fertilizer Mixing System

2024-06-03 , Wan Mohd Faizal Wan Nik , Shahrul Fazly Man@Sulaiman , Muhammad Imran Ahmad , Shafie Omar , Tan Shie Chow , Mohd Nazri Abu Bakar , Fadhilnor Abdullah , Muhammad Khamil Akbar

Agriculture techniques, particularly fertilizer mixing, have significant impacts on crop productivity. Introducing IoT technology to agriculture can enhance productivity, and machine learning offers a mechanism to gain insights from data, making agricultural practices more efficient. This research aims to design an AI-assisted and IoT-based fertilizer mixing system for greenhouses. This system utilizes sensor data and AI algorithms, specifically the Support Vector Machine (SVM), to optimize fertilizer application. Results from the SVM classifier showed a 100% accuracy rate for temperature and humidity, 65% accuracy for phosphorus, 86% for nitrogen, and 100% for potassium. These findings demonstrate the potential of the proposed system to improve fertilizer efficiency while reducing labor and resource waste.

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Effects of Cutouts on Energy Absorption Characteristics of Thin-walled Tube Impacted under Dynamic Loading

2022-12 , M. H. Zikri , M. Ahmad , Muhamad Nur Misbah , Wan Mohd Faizal Wan Nik , Mohd Al-Hafiz Mohd Nawi , Mohd Haidiezul Jamal Ab Hadi , Mohd. Hazwan Mohd. Hanid

A thin-walled tube is an energy absorber device that is commonly used in automotive and locomotive applications. The function of this element is to convert the kinetic energy into other forms of energy during a collision that can minimize injuries to the passengers. Therefore, various studies have been reported previously to improve the thin-walled structure to decrease the damage and provide protection for the vehicle and occupant. This study aims to determine the effects of the cutout on the thin-walled tube when impacted under dynamic axial loading. The effects of sizes, shapes, locations, and the number of cutouts on the energy absorption characteristics have been analyzed by using the validated finite element model. The result indicates that a circular tube with a square cutout shape, larger cutout sizes, and near the top-end of the tube has more energy absorption characteristics. Furthermore, the results of energy absorption (EA), crush force efficiency (CFE), and specific energy absorption (SEA) are highest when applying four cutouts on the surface of the thin-walled tube. Research information provided in this study will serve as a guide in designing the cutout thin-walled tube for crashworthiness enhancements in the future.

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Solar light emitting diode (LED) street lighting with automatic vehicle detection system

2014 , Wan Mohd Faizal Wan Nik

This thesis is about a development and fabrication of solar light emitting diode (LED) street lighting with an automatic vehicle detection system. Present available solar street lightings are operated based on the timer or light sensor which continuously turns on during night time even though the street is empty i.e. without any vehicle passing through it. To overcome this problem a system that was able to detect a vehicle at night using light dependent resistor (LDR) and microcontroller was designed. The microcontroller controlled the whole operation of the system, including the charging and discharging of the battery and the illumination of the LED lamp. The project comprises of the development of the DC to DC boost converter, dark and vehicle detection sensor and LED lamp driver. The boost converter system was designed to overcome the problem due to the lower output voltage from the solar panel compare to the optimum level of batteries charging voltage. From the experiment the output voltage from this DC to DC boost converter was 14.5 volts which is the optimum charging voltage. The vehicle and weather condition was detected by the vehicle and dark sensors. The test determined the distance of the incoming vehicle that the sensor can detect. During low beam testing the sensor managed to detect a vehicle at 80m away from it. For the high beam the vehicle detected by the sensor at 170m from it. In order to turn on the LED lamp, a DC relay system was developed. This relay controlled the electrical supply from batteries to the LED lamp. The complete circuit for this system was developed on the printed circuit board (PCB). The experimental results show that the system can charge the battery from 20% to 100% within a day. The battery chose was adequate to supply enough power to the load for 10 hours. The incoming vehicle on the street can be detected by vehicle sensor. While the dark sensor can distinguish between day and night condition.

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