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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Innovating household efficiency: the internet of things intelligent drying rack system Othman, Norhalida; Mohd Yusoff, Zakiah; Khamis @ Subari, Mohamad Fadzli; Muhamad, Nur Amalina; Khairul Anuar, Noor Hafizah
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.pp99-106

Abstract

The intelligent drying rack system (IIDRS) proposes an innovative approach to modernize clothes drying practices using internet of things (IoT) technology. Combining an Arduino Uno microcontroller, ESP8266 for data transmission, and an array of sensors including limit switches, light dependent resistors (LDRs), rain sensors, and temperature/humidity sensors, the IIDRS enables automated control of the drying rack and fan. Its remote accessibility via Blynk apps allows users to conveniently adjust settings and monitor drying progress. By autonomously adjusting drying cycles based on real-time environmental conditions, the IIDRS enhances efficiency and minimizes inconveniences such as wet clothes during rainfall. Moreover, it contributes to sustainable living by optimizing energy consumption through weather-based operation. With its intuitive interface and compatibility with modern lifestyles, the IIDRS represents a significant advancement in smart home solutions, showcasing the transformative potential of IoT technologies in everyday tasks.
Boxplot analysis of 4 grade agarwood essential oil for various grades Hasnu Al-Hadi, Anis Hazirah 'Izzati; Mohd Amidon, Aqib Fawwaz; Mohd Huzir, Siti Mariatul Hazwa; Ismail, Nurlaila; Mohd Yusoff, Zakiah; Tajuddin, Saiful Nizam; Taib, Mohd Nasir
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp238-244

Abstract

Agarwood essential oil is used in most perfumery ingredients, as an incense and in traditional medical preparations. Agarwood essential oil, called "Black Gold," is extremely valued to the global community due to its numerous benefits. As of now, there is still no standard technique of grading different grades of agarwood essential oil. The current grading technique is inefficient since the agarwood essential oil is graded by using human sensory panel. Different people might have different perspective on grading the agarwood essential oil hence, the technique is not practical to adapt it globally. Due to the current technology, numerous intelligent techniques for verifying the grades of agarwood essential oil have been proposed and implemented. The study has conducted a statistical analysis on 4 grade agarwood essential oil using boxplot. Boxplot analysis summarizes the abundances for each chemical compounds from four different grades of agarwood essential oil with a high grade as a reference. This study shows the analysis of boxplot investigated 10-epi-δ-eudesmol, α-agarofuran, β-agarofuran, δ-eudesmol and dihydrocollumellarin as most important chemical compounds in high grade of agarwood essential oil. The chemical compounds that have been identified in high grade of agarwood essential oil can be a reference for future research studies.
Wireless hand motion controlled robotic arm using flex sensors Mohd Yusoff, Zakiah; Aminah Nordin, Siti; Munira Markom, Arni; Nadia Mohammad, Nurul
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp133-140

Abstract

In today's world, in almost all industries, much of the work is performed by robots or robotic arms with varying degrees of freedom (DOF) as necessary. The aim of this study is to adjust the perception of remote controls for manually controlled robotic-arm operation. This paper offers a way of thinking and a way to eradicate the keys, joysticks and replace them with some of the more intuitive strategy that is to operate the full robotic arm by hand movements operators. The robotic arm is constructed in such a way that it consists of two movable fingers and other movement, which is, a spreading elbow and the up down movement. The robotic arm is designed to mimic the motions of human hands using a hand glove. The hand glove consists of 3 flex sensors for controlling the motions of the finger, the elbow, and other movements. Servo motors are the actuators used by the robotic arm. The proposed electronics device recognizes a basic hand gesture that will be made in real lifetime and will relay valued signals wirelessly through the RF module.
The significance of artificial intelligent technique in classifying various grades of agarwood oil Fawwaz Mohd Amidon, Aqib; Mariatul Hazwa Mohd Huzir, Siti; Mohd Yusoff, Zakiah; Ismail, Nurlaila; Nasir Taib, Mohd
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp261-269

Abstract

Agarwood oil quality is often separated into two or three categories. This makes classifying agarwood oil quality using current methods difficult. Current approaches rely solely on human perception to determine the quality of agarwood, whether in raw material or oil. This technique has other undesirable implications. It can affect the human sensory system, particularly the eyes and nose. Categorization takes time, which is a considerable expense to succeed in this method. As a result, a new classification system should be devised. The chemical components in agarwood oil are used to classify it in this study. In this study, samples with preprocessing data from two to five quality levels were used. The purpose is to categorize this data based on its qualities and analyze whether this new quality group is acceptable. The K-nearest neighbours (KNN) approach was used to classify all samples and their properties for this dataset. All samples may be correctly classified by grade without any errors. This shows the chemical compound-based classification of agarwood oil can be retained. With these findings, future agarwood oil research may focus on building a new classification.