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All Journal International Journal of Advances in Applied Sciences Indonesian Journal of Electrical Engineering and Computer Science
Thamrin, Norashikin M.
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Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Colour sorting ROS-based robot evaluation under different lights and camera angles Saaid, Mohammad Farid; Thamrin, Norashikin M.; Misnan, Mohamad Farid; Mohamad, Roslina; Romli, Nurul A’qilah
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i3.pp1807-1815

Abstract

Automated colour sorting, aided by mobile robots, is widely prevalent in the current manufacturing industry. Obstacles, such as fluctuating light conditions and camera angles, frequently hinder this procedure. Creating a colour sorting robot is a complex and time-consuming task, especially due to the vulnerability of the RGB colour space to detection errors in extreme brightness or darkness. In response to these concerns, we introduce a mobile robot that operates on the robot operating system (ROS) platform and incorporates OpenCV. This robot employs the hue, saturation, and value (HSV) colour space model for its image processing capabilities in recognising the colours and Welzl’s algorithm for the ball’s diameter estimation. The robot’s performance was assessed across various luminous fluxes and camera tilt angles. It demonstrated exceptional performance at 64 lm and a tilt angle of 40 degrees, achieving an average accuracy of 87.5% for detecting the colour of the ball, and 81.25% for determining its location based on colour. For the ball’s diameter estimation, it was found that the best estimation was received at 64 lm and 30 degrees, with both 96.32%.
Solar-powered irrigation and monitoring system for okra cultivation Soekarno, Mohamad Syfiq; Mohamad, Roslina; Thamrin, Norashikin M.; W. Muhamad, Wan Norsyafizan
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp469-477

Abstract

Eco-friendly and cost-effective irrigation systems are essential for sustainable agriculture. Traditional irrigation systems are unsustainable due to the high cost of operation and environmental pollution associated with fossil fuels. A possible solution for farmers is the use of solar-powered irrigation systems. This research aims to develop a solar-powered irrigation and a real-time monitoring system for okra cultivation. The irrigation system was powered by a monocrystalline solar panel and controlled by a Node MicroController Unit ESP8266 microcontroller unit. A 12 V pneumatic diaphragm water pump was utilized to irrigate the okra plants efficiently. The real-time monitoring system using Blynk allowed for the remote monitoring of the system's performance. The irrigation system was deployed on an okra farm, and the results showed that the system could sustain the soil moisture level for the okra plants, with an average soil moisture sensor reading of over 80%. The system delivered power effectively, with an average voltage measurement exceeding 12 V, average current readings above 180 mA, and average power readings exceeding 2 W. These results demonstrate that the solar-powered irrigation system is a viable and sustainable solution for farmers, researchers, and engineers to enhance the performance of conventional irrigation systems.
EMG-based hand gesture classification using Myo Armband with feedforward neural network Mohd Said, Sofea Anastasia; Thamrin, Norashikin M.; Amin Megat Ali, Megat Syahirul; Hussin, Mohamad Fahmi; Mohamad, Roslina
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp159-166

Abstract

This paper presents the development of an electromyography (EMG)-based hand gesture identification system for remote-controlled applications. Even though the Myo Armband is no longer commercially supported, the research discusses its use in EMG data collecting. Open-source libraries were utilized to capture EMG data from this device to solve this problem. Using the developed data acquisition platform, data was collected from 30 participants who performed three (3) gestures - a fist, an open hand, and a pinch. The energy spectral density (ESD) and power ratio (pRatio) were extracted to describe gesture-specific patterns. A feedforward neural network (FFNN) was implemented for classification, initially configured with 10 hidden neurons and later optimized to 40 neurons to improve the performance. The box plot analysis showed channels CH1, CH4, CH5, and CH7 as the most significant for enhancing classification accuracy. The optimized FFNN achieved 80% and 70% for the training and testing accuracies, respectively. However, the results suggest that implementing a systematic protocol during data acquisition to reduce signal overlap between movements could improve classification accuracy. In conclusion, the study successfully developed an open-source EMG data acquisition platform for MYO Armband and demonstrated acceptable hand gesture recognition using an optimized FFNN.
Evaluating telemedicine diabetes mellitus: a mobile health app for type-2 diabetes Karim, Muhammad Zakwan Abdul; Thamrin, Norashikin M.; Shauri, Ruhizan Liza Ahmad; Jailani, Rozita; Manaf, Mohd Haidzir Abd; Mustapa, Nurul Amirah
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp787-795

Abstract

Telemedicine diabetes mellitus (Tele-DM) mobile health (mHealth) tool functionality, usefulness, and user feedback were examined in this study. Data from nine distinct users of type-2 diabetes (T2D) patients, healthcare professionals (HCPs), and administrators was analyzed to determine functionality. Data retrieval times increased with database user data amount, according to the study. A 3-month program with five T2D patients reduced weight (0.98 kg) and Hemoglobin A1c (HbA1c) (0.34%). This shows that Tele-DM helps manage diabetes, but more participants are needed to confirm. Nine Tele-DM customers were satisfied with the app's reception, according to 14 online questionnaires. Overall, Tele-DM simplifies diabetic self-management in a novel way. This study shows its potential to transform diabetes management and address major healthcare issues.
Co-Authors Amin Megat Ali, Megat Syahirul Hussin, Mohamad Fahmi Karim, Muhammad Zakwan Abdul Manaf, Mohd Haidzir Abd Misnan, Mohamad Farid Mohamad, Roslina Mohd Said, Sofea Anastasia Mustapa, Nurul Amirah Romli, Nurul A’qilah Rozita Jailani, Rozita Saaid, Mohammad Farid Shauri, Ruhizan Liza Ahmad Soekarno, Mohamad Syfiq W. Muhamad, Wan Norsyafizan