Roejhan Md Kawi
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Preferred name
Roejhan Md Kawi
Official Name
Roejhan, Md Kawi
Alternative Name
Kawi, R. Md
Main Affiliation
Scopus Author ID
57221203782

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Fusion wind and solar generation forecasting via neural network

2021-08-27 , Mahmoud Mustafa Yaseen Mohammed Al Asbahi , Muhammad Naufal Mansor , Mohd Rizal Manan , Mohd Azri Abd Aziz , Roejhan Md Kawi , Farah Hanan Mohd Faudzi

Wind and solar power are the most common renewable resources of energy and their usage for power generation is quickly growing all over the world. However, both wind and solar power are difficult to predict manually due to every time changes in weather condition; therefore. power output of wind and solar is associated with some uncertainty. A reliable wind-solar day ahead load prediction proposed in this paperwork to support a small microgrids system. The system is a combination of hardware of solar panel, wind turbine, hybrid charge controller, current sensor, voltage sensor circuit, battery, Arduino Mega and personal computer that is install with MATLAB along with artificial neural network model for load forecast. The prediction model is known as Feedforward back propagation (FFBP) artificial neural network (ANN), this method utilizes a learning relationship between wind-solar power output and predicted weather. The FFBP model trained ANN to recognize similar pattern and to predict the output power based on train and tested data and the results achieved 99.5 accuracy, 6.25% MAPE and 1.2 % MAD.

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System Design for Early Detection of Explosive and Flammable Gas Leaks Using Mobile Robot in Confined Space

2021-12-01 , Muhammad Aizat Abu Bakar , Mohd Rizal Manan , Roejhan Md Kawi , Yunn, L. J.

The presence of explosive or flammable gases in confined space may contribute towards accidents that threaten the workers safety and industrial progress. Conventionally, the existing instrument for gas detection in confined space is manually carried by humans whereby the workers or competence person itself were exposed directly to the gases. This project is aim to develop a prototype system to detect the presence of gases leak where the robotic system replaces humans to carry gas sensors. Users only need to maneuver the robot using a mobile phone to monitor the specific area that may have an explosive or flammable gas leak which includes Liquefied Petroleum Gas (LPG) and methane gases. The sensors will detect if a change in the gas concentration has exceeded a safety limit and will activate the alarm as an alert signal. The readings of gases as input signals were sent wirelessly to the Personal Computer (PC) as a user device for monitoring purposes. This prototype is successfully developed, tested and calibrated using the samples of LPG gas, methane, smoke and environment temperature. The result proved that the developed system is able to detect an air sample using selected gas sensors and display the data in graph form with live monitoring. This will contribute significantly to acquiring a new and alternative method using the system for detecting the presence of gases in confined space application.

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Development of Surveillance Hovercraft via Arduino

2024-02-01 , Muhammad Naufal Mansor , Syahrul Affandi Saidi , Wan Azani Wan Mustafa , Roejhan Md Kawi , Mohd Aminudin Jamlos , Talib N.A.A. , Mohd Zamri Hasan

The current research focuses on the development of hovercraft via Arduino. The vehicle is designed with bag skirt structure in order to reduce friction for smooth operation. Nowadays, there are a lot of natural disaster occur in everywhere especially flood. However, hovercraft is a vehicle that need a driver to drive which can cause a danger to the rescuer. Based on this problem, a wireless hovercraft is needed to develop. This study explains a hovercraft which is able to control the movement of the hovercraft from the surface. The design of the hovercraft was successfully made by using AutoCAD software. Furthermore, the material of the body was made from the insulation foam while the microprocessor is Arduino UNO R3. There are two brushless DC motors and one servo motor that used for this hovercraft. The first brushless DC motor which is located below the hovercraft is used as a hover operation, while the second motor located behind it is used to ensure the hovercraft move forward. In addition, the performance of the hovercraft was successfully tested on the 3 different surfaces. As a result, the highest performance is on the cement while the lowest is on the grass.

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Ergonomic intervention in harvesting process in oil palm plantation

2016 , Roejhan Md Kawi

Most fannworkers in the small and medium Oil palm industry are using conventional method for harvesting works. Therefore, they are extremely exposed to the risk of shoulder muscle injury which is one of the musculoskeletal disorders (MSDs) problems. Referring to the Rapid Upper Limb Assessment (RULA), conventional harvest works was highly risk to undergo shoulder muscle problem due to extreme harvest posture with the repetitive and high of loading. Based on the body score result, there were 100% of respondent proven suffering shoulder problem. Hence the aim of this project is to identify proper working posture with design of palm oil harvesting ergonomic intervention device in order to replace the use of long arm sickle in conventional harvest. A comprehensive field study was conducted which focusing on conventional harvest posture by using Electromyography (EMG). Five male subjects volunteered to demonstrate these harvest posture conditions with four selected muscle activity and recorded by EMG and the signal data then plotted into scatterplot. By these findings, the analytical expression developed with proper harvest posture basis as a motivation in designing the intervention. The intervention is developed into prototype with mechanism system. A prototype field evaluation has been conducted to monitor the muscles activities with focus on same selected muscle by using EMG. Volunteered farmworkers is randomly picked to demonstrate the hruvesting process. The result shows reduction of selected muscle activity as compared to the conventional method due to working posture improvement. The Human Activity Analysis (HAA) was study to investigate the posture of the farmworkers during conventional and intervention harvest. There are five body conditions were simulated: L4- L5 compression, body load compression, axial twist compression, flex/ext compression and L4-L5 joint shear. Besides, the RULA's also shows better score as concrete evidence in improving body posture during harvesting work with this new method. As conclusion, optimized working posture along with the assistance of intervention prototype in oil palm harvesting process is suggested since the data provided in this research shows it could decrease the risk of shoulder muscle pain. This research also encourage of generating the innovation in designing new tools to increase the agriculture workers petformance.

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Adaptive PD Controller Performance for Direct Cooling of Thermoelectric Refrigerator

2020-12-18 , Mohd Saifizi Saidon , Mohd Rizal Manan , Baseemah Mat Jalaluddin , Lee T.W. , Junaidah Ali Mohd Jobran , Roejhan Md Kawi , Mat Piah M.S. , Diana N.S. , Wan Azani Wan Mustafa

Refrigerator is the key component to keep the medicine and biological sample in the hospital. The domestic refrigerator has the problem of larger size and heavier weight since to the compact system like condenser, compressor, evaporator and expansion valve are assemble and using in the refrigerator. This project focused on design of temperature control of the portable thermoelectric refrigerator for medical purpose. Thermoelectric refrigerator is using the direct cooling method through thermoelectric module. Thermoelectric refrigerator has several advantages such as smaller size, lighter and silent when operated. Since maintain a constant temperature for the storage of medical product is important, a specific refrigerator is needed to ensure the medicine is stored in desired temperature. This project is to design and develop an adaptive control system which can perform a good temperature control for the thermoelectric refrigerator. The second order model is applied to design adaptive Proportional-Derivative (PD) controller. The selected controller is the adaptive PD controller because the performance of response shows 0.42 C of less steady state error and 0.21 C of lower undershoot. The adaptive PD control system designed able to let the refrigerator operate in different operating condition without influence the performance of the refrigerator.

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Fusion wind and solar generation prototype design with Neural Network

2021-08-27 , Mahmoud Mustafa Yaseen Mohammed Al Asbahi , Muhammad Naufal Mansor , Mohd Rizal Manan , Mohd Azri Abd Aziz , Roejhan Md Kawi , Farah Hanan Mohd Faudzi

Wind and solar power are the most common renewable resources of energy and their usage for power generation is quickly growing all over the world. However, both wind and solar power are difficult to predict manually due to every time changes in weather condition; therefore, power output of wind and solar is associated with some uncertainty. A reliable wind-solar day ahead load prediction with neural network was proposed to support a small microgrids system. All the system performance measurement such as sensitivity, specificity and accuracy give higher than 90%.

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