Mohamed Mydin Hj M.Abdul Kader
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Preferred name
Mohamed Mydin Hj M.Abdul Kader
Official Name
Mohamed Mydin , Hj M.Abdul Kader
Alternative Name
Kader, M. M.A.
Abdul Kader, M. Mohamed Mydin
Mohamed, M. M.A.K.
Abdul Kader, Mohamed Mydin M.
Kader, M. M.M.A.
Main Affiliation
Scopus Author ID
57202264868
Researcher ID
CYH-3060-2022

Research Output

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Reprogramming the articulated robotic arm for glass handling by using Arduino microcontroller

2017-09-26 , Zol Bahri Razali , Mohamed Mydin Hj M.Abdul Kader , Mohd Asmadi Akmal Kadir , Mohd Hisam Daud

The application of articulated robotic arm in industries is raised due to the expansion of using robot to replace human task, especially for the harmful tasks. However a few problems happen with the program use to schedule the arm, Thus the purpose of this project is to design, fabricate and integrate an articulated robotic arm by using Arduino microcontroller for handling glass sorting system. This project was designed to segregate glass and non-glass waste which would be pioneer step for recycling. This robotic arm has four servo motors to operate as a whole; three for the body and one for holding mechanism. This intelligent system is controlled by Arduino microcontroller and build with optical sensor to provide the distinguish objects that will be handled. Solidworks model was used to produce the detail design of the robotic arm and make the mechanical properties analysis by using a CAD software.

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Methylene blue dye adsorption by using deep eutectic solvent pre-treated wood chips

2022-11-18 , Muhammad Masrur Jamil , Ahmad Anas Nagoor Gunny , Mohd Sharizan Md Sarip , Mohd Faizal Ab Jalil , Mohamed Mydin Hj M.Abdul Kader , Mohamed Syazwan Osman , Zulkarnain Mohamed Idris

Adsorption of Methylene Blue using biomass or bioproduct of industries has received major attention by the researcher and industries. In this study, wood chips treated using deep eutectic solvents (DES) was used for adsorption of methylene blue. The surface and pores of this wood chips were analyzed by using scanning electron microscope (SEM). One Factor At a Time (OFAT) method was carried out to study the effect of contact time and biomass dosage on adsorption efficiency. Evaluation of pretreated wood chips biosorption, isotherms and kinetics were also studied.. Wood chips treated with DES changes the surface area and the pores of wood chips and improved the adsorption process efficiency. Freundlich isotherm and pseudo-second show correlation coefficient of R2, 0.9591 and 0.9999 respectively. Wood chips treated using deep eutectic solvents demonstrate a great potential as a cheap biosorbent for the removal of methylene blue by looking at the isotherm and kinetic studies.

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Aquaponic Ecosystem Monitoring with IOT Application

2023-08-01 , Muhammad Naufal Mansor , Mohd Zamri Hasan , Mohamed Mydin Hj M.Abdul Kader , Wan Azani Wan Mustafa , Syahrul Affandi Saidi , Mohd Aminudin Jamlos , Noor Anida Abu Talib

Aquaculture is an agricultural technology that combines aquaculture (fish farming activities) with hydroponic activities (planting crops without soil media) in one circulation. The most important element in aquaculture is the existence of fish, plants, and bacteria. These three elements form a mutually beneficial relationship or symbiotic mutualism. The main purpose of the aquaculture system is to maintain water quality and reduce ammonia levels from the water so that it can be utilized by other organisms. In addition, aquaculture can also save space and can produce two types of human food simultaneously, plants and livestock. Agricultural technology design with Aquaculture also uses the concept of Internet of Things (IoT) as information from sensors and sensors of value generator is accessible through applications installed on smartphones from anywhere with an Internet connection. Development of monitoring of aquaponic ecosystems with IoT systems was developed using a program using micro-controls to control temperature, humidity, pH levels and water pumps. There are some improvements made to this project.

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Characterizing Global Hand-Crafted Feature Descriptors for Sketch-Based Image Retrie

2022-02-14 , Abbas M.H. , Che Ani A.I. , Abd Samat A.A. , Hazim M.A. , Mohamed Mydin Hj M.Abdul Kader , Setumin S. , Muhammad Faisal Hamidi @ Abdul Rani

Sketch-based Image Retrieval (SBIR) is an essential method of searching objects by drawing them in two-dimensional (2-D). The SBIR problem was that the image inside the dataset did not match the pair due to its modality difference. The main objective of this research is to compare which descriptor is better adapted to the SBIR. Histogram of Oriented Gradient (HOG), Gabor, and Local Binary Pattern (LBP) are selected for the study. Each sample will be divided into distance measures with features vector that corresponds to the training dataset will be compared the performance in order to study the best adapted to SBIR. Histogram of Oriented Gradient (HOG) is identified as the best descriptor for SBIR. HOG has shown a better performance than Gabor and LBP since the method shows the highest percent of distance matrices accuracy.

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Environmental lighting towards growth effect monitoring system of plant factory using ANN

2025-01 , Mohamed Mydin Hj M.Abdul Kader , Muhammad Naufal Mansor , Wan Azani Wan Mustafa , Ahmad Anas Nagoor Gunny

Malaysia is currently driven to become another most developed country in the world. Among other priority sector is Food Sustainability. Along the process, our vegetable supply-demand keeps increasing by year. Compared to traditional systems, closed systems or its other name called hydroponic is getting more important for plant production, with artificial light which has many potential advantages, including better quality transplants, shorter production time and less resource use. To gain full profit from it, the quality of vegetables needs to be controlled efficiently. Climate conditions, especially temperature and light intensity, have a significant impact on vegetable growth and yield, as well as nutritional quality. Plant growth and development are influenced by a variety of environmental factors, the most important one is light intensity. Among the problems to be tackled in this research are plant growth manual observation, light intensity variation and abundance of growth-related data to be evaluated manually. Therefore, to solve these problems, the specific type of vegetable used here is lettuce. The proposed methods are, observation of plant growth conducted automatically round the clock in intervals of 15 minutes for the whole month (estimated mature period of lettuce), using images captured. At the same time, the proposed light intensity which is red & white to the ratio of 2:1 (optimum ratio recommended by previous researchers) will be used. The issue of data to be evaluated manually will be solved using Artificial Neural Network (ANN) architecture, in specific Deep Learning. Concisely, the results & analysis shows the research is successfully developed for plant growth monitoring by using artificial neural network which, reached 80% to 90% accuracy in the training and validation session that made the architecture sufficient for determining the growth of the said vegetable. This is indeed foreseen, will highly assist the farmer in better monitoring the growth rate of the plant.

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Automotive Mechanical Vehicle Starter

2021-12-01 , Mohamed Mydin Hj M.Abdul Kader , Zol Bahri Razali , Wan Azani Wan Mustafa , Syahrul Affandi Saidi , Ahmad Anas Nagoor Gunny , Setumin S. , Osman M.K. , Idris M. , Akbar M.F. , Muhammad Anas Ahmad Sarbini , Nor Syamina Sharifful Mizam

This research is used to crank start automotive vehicle. There are many different system used in order to start-up vehicles using electric starter, in the time of battery low-power or totally drained. The purpose of this research is to help the driver to get out of this difficulty. Nowadays there are many people that have experienced such a bad moment, where they are stranded at road side due to malfunction starter in their car because of battery problem. Most of the vehicle electric starter failure is because of battery corrosion or battery undercharged. The importance of this research is to solve this problem. Starter is a vital part of the vehicle, without it no automotive vehicles able to operate. These starters will rotate an internal-combustion engine to initiate the engine's operation under its own power. Starters also can be malfunction too due to corroded electrical connections or an undercharged battery. This system can be used to solve this problem. This system used human energy by using mechanical parts in order to produce electrical power. In order to produce electrical current, workforce will be applied by rotating the wheel that already linked by belt and from that rotations will trigger a magnetic force and it will produce an electrical current and supply it into battery. This system is divided into two development; hardware development and software development. The hardware development involved, mechanical device which is used and electrical device such as monitor. For software development, Fritzing is used to construct circuit.

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Design and analysis on robotic arm for serving hazard container

2017-09-26 , Zol Bahri Razali , Mohamed Mydin Hj M.Abdul Kader , Khoo Zern Yi , Mohd Hisam Daud

This paper presents about design, analyses development and fabrication of robotic arm for sorting multi-material. The major problem that urges the initiation of the project is the fact that manufacturing industry is growing at relatively faster rate. Most of the company produce high load robotic arm. Less company creates light weight, and affordable robotic arm. As the result, light weight and affordable robot is developing to cover this issue. Plastic material was used to construct the body of the robotic arm, and an optical sensor was implemented to provide basic recognition of object to be carried. The robotic arm used five servomotors for overall operation; four for its joints, and one for the gripping mechanism. The gripper was designed and fabricated using Perspex due to the light weight and high strength of the material. The operation of the robotic arm was governed by Basic Stamp programming sequence and the device was expected to differentiate material and other objects based on reflective theory, and perform subsequent operations afterwards. The SolidWorks was used to model the detail design of the robotic arm, and to simulate the motion of the device.

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Electronic Nose Testing for Confined Space Application Utilizes Principal Component Analysis and Support Vector Machine

2020-12-18 , Muhammad Aizat Abu Bakar , Abu Hassan Abdullah , Wan Azani Wan Mustafa , Zol Bahri Razali , Syahrul Affandi Saidi , Mohamed Mydin Hj M.Abdul Kader , Aman M.N.S.B.S.

A confined space has a limited space for entry and exit but it is large enough for workers to enter and perform work inside. It is not designed for continuous occupancy because it can contribute atmospheric hazards accidents that threaten the worker safety and industry progress. In this work, we reported the testing an instrument to assist workers for atmosphere testing during pre-entry. An electronic nose (e-nose) using specific sensor arrays is the integration between hardware and software that able to sense different concentrations of gases in an air sample using pattern recognition techniques. The instrument utilizes multivariate statistical analysis which is Principal Component Analysis (PCA) for discriminate the different concentrations of gases and the Support Vector Machine (SVM) to classify the acquired data from the air sample. The instrument was successfully tested using diesel, gasoline, petrol and thinner. The results show that the instrument able to discriminate an air sample using PCA with total variation for 99.94%, while the classifier success rate for SVM indicates at 98.21% for train performance and 95.83% for test performance. This will contribute significantly to acquiring a new and alternative method of using the instrument for monitoring the atmospheric hazards in confined space to ensure the safety of workers during work progress in a confined space.

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Urban farming growth monitoring system using Artificial Neural Network (ANN) and Internet of Things (IOT)

2025-01 , Mohamed Mydin Hj M.Abdul Kader , Muhammad Naufal Mansor , Wan Azani Wan Mustafa , Ahmad Anas Nagoor Gunny

As an introduction to this project, the growth-related traits, such as above-ground biomass and leaf area, are critical indicators to characterize the growth of indoor lettuce plants. Currently, non-destructive methods for estimating growth-related traits are subject to limitations in that the methods are susceptible to noise and heavily rely on manually designed features. It is also one of the problem statements in this project. Based on this project the next problem is manual control of nutrients may cause quality issues to the lettuce plant. If the nutrient supply is too much or less, it will disturb the growth of the lettuce plant either the lettuce plant is dead or stunted. This project is about urban farming growth monitoring system using Artificial Neural Network (ANN) and Internet of Things (IoT). In this project, a method for monitoring the growth of indoor lettuce plants was proposed by using digital images and an ANN using Deep Learning Architecture. DLA is mostly developed by the software of MATLAB or Python to insert and run the coding. DLA is mostly used for image detection, pattern recognition, and natural language processing through the graph for Neural Network. Next, the Internet of Things (IoT) is a medium to store images of indoor lettuce plant growth into the Cloud (Google Drive). Furthermore, it takes indoor lettuce plant images as the input, an ANN was trained to learn the relationship between images and the corresponding growth- related traits with other fixed parameters. The pH level parameters were controlled by other fixed parameters to take the images of indoor lettuce plant growth. The parameters used in this project are temperature and humidity. This helps to compare the results of Artificial Neural Network (ANN), widely adopted methods were also used. Concisely, this project is expected to develop the Deep Learning Architecture using an Artificial Neural Network (ANN) with digital images as a robust tool for the monitoring of the growth of indoor lettuce plants every 30 minutes per day. Generally, focused on an urban farming growth monitoring system using Artificial Neural Network (ANN) and the Internet of Things (IoT).

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Renewable Energy Driven Exhaust Fan for Use in Laboratory via IOT

2021-01-01 , Mohamed Mydin Hj M.Abdul Kader , Wan Azani Wan Mustafa , Akbar M.F. , Syahrul Affandi Saidi , Ahmad Anas Nagoor Gunny , Zol Bahri Razali , Osman M.K. , Setumin S. , Idris M. , Mahendran Gunaseakaran , Nor Syamina Sharifful Mizam

This paper discussed on the hardware product of renewable energy driven exhaust fan for use in laboratory via IOT. Ventilation is generally deployed in buildings for maintaining user's safety and health. This renewable energy driven exhaust fan is the most considered system in improving the energy saving while sustaining user's safety and health. If we can renew and reuse the energy we waste, it would help in some way to the problem of scarcity of energy, which is major threat of present world. Initial capital cost of solar systems is still quite high when it comes to generate power for domestic. By using the concept of wind turbines wind-generated electricity can be used for battery charging and for connection with the power grid. Hence this research proposes a prototype of Renewable Energy Driven Exhaust Fan for use in laboratory via IOT. This research presents a prototype of regenerating power by an exhaust fan. The generated power can be either used directly or can be stored in a battery. This exhaust fan also can be controlled and monitored via IOT. The objectives of this research are, to design and develop an exhaust fan that can be driven by renewable energy, to design and develop an exhaust fan that can be controlled by IoT and to collect data and analyze the power consumptions and power saving. Methods used in this research is to use power from battery to operate the Fan 1. Than this kinetic energy produced by Fan 1 is used to drive Fan 2 and Fan 3 which are now actually a pair of generators with the help of charging circuit to directly recharge the battery which at first used to power up Fan 1. Analysis is then carried out to evaluate the theory, which actually agreed to the initial theory as presented

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