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28,188 Article Results

Design and implementation of Internet of Things-enabled long-range autonomous surveillance bot for LPG leak detection and environmental safety monitoring

10.11591/ijra.v14i3.pp361-369
Rajesh Singh , Anita Gehlot , Rahul Mahala , Vivek Kumar Singh
Liquefied petroleum gas (LPG) accidents pose significant safety risks, requiring continuous monitoring and Internet of Things (IoT) technology to prevent gas leakage and ensure human safety. This work proposes distributed field-oriented IoT gas sensing robots for detecting dangerous flammable gases like Ammonia, Sulphur Dioxide, Nitrogen Dioxide, and Carbon Dioxide. The SnoLURk solution enables cost-effective IoT gas leak detection in indoor and outdoor robots using budget-friendly casings and sensors. The study also discusses a robotic system for gas leak detection, aiming to detect and combat burglary using ZigBee and GSM modules. Cloud support allows Wi-Fi zone residents to receive alerts and send investigators via email, enabling remote data analytics monitoring. The IoT-based Worker's Health Monitoring System improves health and safety practices in industrial environments by monitoring workers' health 24/7. It allows on-site and off-site monitoring, enabling quick intervention and avoiding complications. The system's applications include construction, mining, manufacturing, and healthcare. Future versions may include improved sensors and machine learning.
Volume: 14
Issue: 3
Page: 361-369
Publish at: 2025-09-01

River cleaning robot using Arduino microcontroller

10.11591/ijra.v14i3.pp332-338
Dubala Ramadevi , Kalagotla Chenchireddy , Barkam Rekha , Sunkari Prathyusha , Koriginja Shravani , Karnati Bhargavi
River cleaning robots represent a promising technological solution to address the pervasive issue of water pollution in river systems. These autonomous devices are designed to collect and remove various types of debris from river environments, contributing to improved water quality and ecosystem health. This abstract summarizes the key aspects of river cleaning robots, including their technological advancements, operational mechanisms, and environmental impact. River cleaning robots have evolved significantly from early mechanical designs to sophisticated autonomous systems. Initially, these robots were equipped with basic skimming and collection mechanisms. Recent advancements have incorporated state-of-the-art technologies, including artificial intelligence, machine learning, and advanced sensor systems. Modern river cleaning robots can autonomously navigate complex river environments, detect and classify different types of debris, and operate efficiently with minimal human intervention. The operational capabilities of these robots are enhanced by various design features such as mobility systems, debris collection mechanisms, and renewable power sources. Mobility systems allow robots to maneuver through diverse water conditions, while collection mechanisms like nets, scoops, and suction devices enable effective debris removal. Many robots are powered by renewable energy sources, such as solar panels, which contribute to their sustainability and reduce their environmental footprint.
Volume: 14
Issue: 3
Page: 332-338
Publish at: 2025-09-01

Evaluating the development and cutting capacity of a one-square computer numeric controlled milling machine

10.11591/ijra.v14i3.pp451-462
Oluwaseun Kayode Ajayi , Ayodele Temitope Oyeniran , Shengzhi Du , Babafemi Olamide Malomo , Kolawole Oluwaseun Alao , Quadri Ayomide Omotosho , Marvellous Oluwadamilare Fawole , Ayomide Isaiah Lasaki , Godwin Thompson
Traditional subtractive technology is rapidly losing significance with the advent of digital manufacturing technologies, which offer affordable machining with high accuracy and repeatability. Computer numeric controlled (CNC) machining has been around for a while; however, it has been costly to own one. Since the concept of CNC machining is now broadly understood and open-source software is available for control, designers can make use of available local materials to develop cheaper CNC machines. Hence, this presents the evaluation of the design and development of a one-square-meter CNC milling machine. The control was implemented on Arduino Uno, while open-source Universal G-code Sender (UGS) and G-code reference block library (GRBL) were used for the G-code generation and machine control, respectively. The built CNC was calibrated and tested on wood and plastic materials, and the resulting products were acceptable in accuracy up to ±0.02 mm in the first trial, but attained perfect accuracy by the third trial. Multiple tests repeatedly showed that accuracy was maintained. Since the machine is reconfigurable, future work entails automation and incorporating laser cutting capabilities into the machine.
Volume: 14
Issue: 3
Page: 451-462
Publish at: 2025-09-01

Energy efficient clustering and routing method for Internet of Things

10.11591/ijra.v14i3.pp418-428
Bhawna Ahlawat , Anil Sangwan
The Internet of Things is crucial in monitoring environmental conditions in remote areas, but it faces significant challenges related to energy consumption, which affects network longevity and coverage. Clustering has proven effective in prolonging the life of sensor networks. Adaptive clustering in wireless sensor networks allows for more effective cluster organization via real-time rearranging of sensor nodes according to important parameters, which include energy levels and the distance between them. Fruit fly algorithm (FFA) and ant colony optimization (ACO) are emerging as encouraging techniques for creating clusters and establishing paths, respectively. This paper describes the use of the FFA to make the clustering process better by selecting the best cluster head and reducing energy consumption. This paper proposes a novel solution that integrates ACO for establishing paths with FFA for clustering. This method is tested in both homogeneous and heterogeneous settings using MATLAB, comparing its performance with two existing algorithms: low energy adaptive clustering hierarchy (LEACH) and biogeography-based optimization algorithm (BOA). According to the findings, the suggested algorithm performs noticeably better than BOA and LEACH in the context of coverage area and network service period, especially in heterogeneous settings.
Volume: 14
Issue: 3
Page: 418-428
Publish at: 2025-09-01

Faraid distribution calculation using AI-based Quranic chatbot

10.11591/ijra.v14i3.pp393-406
Iman Hafizi Md Zin , Nur Farraliza Mansor , Norizan Mat Diah , Shakirah Hashim , Mastura Mansor
Faraid, Islamic inheritance law, refers to that aspect of Shariah law which is not properly understood and has created issues and impediments in the distribution of estates. This paper discusses the development of an AI-based Quranic chatbot to be used by the public to learn the Faraid rules and automate calculations of inheritance distribution. The chatbot has been developed using natural language processing and a rule-based algorithm, which intends to search and get an accurate interpretation from the user queries, retrieve relevant verses of the Quran, and compute the share of inheritance according to the established Islamic jurisprudence. Fuzzy match identifies and corrects variation in queries, enhancing user interaction, ensuring that it appears more intuitive and accessible. The system processes user input regarding heirs of the deceased, estate value, and debts, and applies Faraid rules to generate accurate distribution results that happen to be web-based platforms of this chatbot. It intends to link traditional Islamic knowledge with modern digital solutions, bringing Faraid calculations closer, more comfortable, faster, and transparent. Through rigorous tests and user feedback will prove above, revealing the chatbot’s potential in understanding the application of Islamic inheritance law and promoting digital engagement in all these through Quranic teachings.
Volume: 14
Issue: 3
Page: 393-406
Publish at: 2025-09-01

SCADA system in water storage tanks with NI vision LabVIEW

10.11591/ijra.v14i3.pp381-392
Kartika Kartika , Misriana Misriana , M. Fathan Naqi , Asran Asran , Misbahul Jannah , Arnawan Hasibuan , Suryati Suryati
Advances in technology have driven the need for efficient water management systems. This study presents a SCADA-based water management system that integrates LabVIEW and Arduino to monitor and regulate water levels and flow rates in a storage tank. The system uses an HC-SRF04 ultrasonic sensor for water level measurement with 99.77% accuracy and an HX710 pressure sensor, which achieves 98.54% accuracy. The LabVIEW interface displays real-time data, giving users an intuitive view of system performance. A proportional integral derivative (PID) algorithm optimizes the water pump through pulse width modulation (PWM), achieving water flow rate control. The Ziegler-Nichols method tunes the PID parameters to Kp = 16.59, Ti = 1.102, and Td = 0.2755. This tuning ensures the system maintains a consistent target flow rate of 4 liters per minute (L/min) with minimal variation. Initial testing showed a 2.5% overshoot but stabilized at the desired flow rate within 10 seconds, indicating effective control. This SCADA system reduces water and energy waste by enabling continuous real-time monitoring and control. The system provides accurate data through a LabVIEW interface, ensuring effective and informed operational decisions. This robust solution supports efficient water management for industrial and environmental applications, contributing to sustainability and resource optimization.
Volume: 14
Issue: 3
Page: 381-392
Publish at: 2025-09-01

Empowering breastfeeding mothers: How self-directed learning boosts confidence-unveiling the two-round Delphi method

10.11591/ijphs.v14i3.25965
Dewi Ariani , Respati Suryanto Dradjat , Kumboyono Kumboyono , Lilik Zuhriyah
Promoting breastfeeding self-efficacy through self-directed learning requires behavior, goal setting, and self-reinforcement. This research aims to collect insights from health professionals on strategies for improving maternal confidence in breastfeeding using self-directed learning and existing knowledge. An in-depth exploration through a two-round Delphi method rooted in the self-efficacy theory of self-directed learning for breastfeeding mothers was conducted, involving expert input and an extensive literature review. Four key documents were identified, each undergoing rigorous expert rating to ensure quality. Six essential elements for health professionals to guide breastfeeding mothers were established, focusing on lactation physiology, successful initiation, confidence building, adversity management, cultural beliefs, and public breastfeeding. Three crucial topics, including prior knowledge, personal attributes, and autonomous processes, were designed to enhance self-efficacy through self-directed learning. In conclusion, the study emphasizes the vital role of health professionals in supporting mothers through comprehensive breastfeeding guidance and encouraging self-directed learning.
Volume: 14
Issue: 3
Page: 1256-1266
Publish at: 2025-09-01

ANFIS and PI based performance analysis of three phase three wire distribution system for THD reduction

10.11591/ijape.v14.i3.pp752-760
Khammampati R. Sreejyothi , J. Jayakumar , P. Venkatesh Kumar
Due to the rising usage of nonlinear loads and power electronic devices in businesses, one of the key power system concerns today is inadequacy of power quality (PQ). This article presents compensation of current harmonics in distribution system in source side by using adaptive neuro fuzzy inferences system (ANFIS) controller. DSTATCOM optimized proportional integral (PI) controller and ANFIS regulator are utilized for DC link voltage regulation. The ANFIS controller showed better performance compared to PI controller during compensating harmonics time. This paper compared two control schemes results PI and ANFIS. Three-phase three-wire inverter is used for DSTATCOM circuit. In the results compared DC capacitor voltage and total harmonic distortion (THD) values of source current. The THD with PI controller is 7.92% while by using ANFIS controller it is reduced to 2.76%. The concert of proposed method is analyzed with MATLAB/Simulink software.
Volume: 14
Issue: 3
Page: 752-760
Publish at: 2025-09-01

Design and analysis of two switch DC-DC converters for E-vehicle applications

10.11591/ijape.v14.i3.pp522-532
Jayanthi Kathiresan , Gnanavadivel Jothimani
A non-isolated DC-DC converter topology is proposed in this paper, which is distinguished by its superior performance and reduced component count in comparison to conventional converter designs. The suggested architecture is especially appropriate for applications demanding a large voltage step-up since it achieves an improved voltage conversion ratio and excellent efficiency. The addition of a voltage-boosting element, which is an inductor combined in series with a switching device, to the source side of a conventional boost converter is a unique feature of the suggested converter. To confirm the converter's operating features, a thorough theoretical analysis has been carried out, including stability and steady-state evaluations. In addition, a hardware prototype with a 200 V output and 100 W power rating was created in order to test the converter's functionality. With a peak efficiency of 94.3%, the prototype showed good agreement with analytical forecasts. The suggested converter is a viable option for renewable energy applications because of its high voltage gain, small size, and efficiency. This is especially true for solar systems and other distributed energy sources, where low component counts and high step-up ratios are preferred.
Volume: 14
Issue: 3
Page: 522-532
Publish at: 2025-09-01

Potential as biogas energy and organic fertilizer: a mixture of rice husks and cow dung on full scale anaerobic digestion

10.11591/ijape.v14.i3.pp533-540
Hashfi Hawali Abdul Matin , Syafrudin Syafrudin , Suherman Suherman , Budiyono Budiyono , Iqbal Syaichurrozi
Rice husk is a biomass that can potentially be converted into biogas energy. In this research, a study was carried out regarding the effect of alkaline pretreatment and then a study related to the potential for developing biogas from rice husks in Indonesia and a study related to the potential utilization of biogas by-products in the form of slurry as solid organic fertilizer. So, the main objective is to determine the effect of alkaline pretreatment of rice husks on the potential development of rice husks as raw material for biogas production on a full-scale anaerobic digestion (AD). Research related to the effect of alkaline pretreatment using 3% NaOH by immersion in the substrate for 24 hours was carried out on a lab scale. The variable TS is set at 27%, C/N ratio is 35, uses a 2-liter digester, and measurements are carried out every other day for 60 days. Furthermore, the up-scale was carried out with an AD fixed dome model with a volume of 6 m3. In this study, it was found that pre-treatment with 3% NaOH increased biogas productivity by 1.6 times higher. The potential for rice husk to be converted into biogas energy can reach 3.5 million liters of biogas by 2022. The by-product of biogas in the form of slurry also has the potential to be used as solid organic fertilizer directly. Parameter tests that have been carried out show that the slurry in biogas from rice husks that have gone through a 60-day AD fermentation process complies with the Indonesian National Standard (SNI) 7763:2018 concerning solid organic fertilizers.
Volume: 14
Issue: 3
Page: 533-540
Publish at: 2025-09-01

Localization and mapping of autonomous wheel mobile robot using Google cartographer

10.11591/ijra.v14i3.pp322-331
Qory Hidayati , Novendra Setyawan , Amrul Faruq , Muhammad Irfan , Nur Kasan , Fitri Yakub
COVID-19 has become a world concern because of the spread and number of cases that have befallen the world. Medical workers are the first exposed group because they have direct contact with patients. So, a vehicle is needed to replace tasks such as logistics, delivery, and patient waste transportation. An autonomous wheeled mobile robot (AWMR) is a wheeled robot capable of moving freely from one place to another. AWMR is required to have good navigation and trajectory control skills. The purpose of this study is to develop an AWMR navigation system model based on the simultaneous localization and mapping (SLAM) algorithm, accurately in a dynamic environment. With this research, developing a good navigation and trajectory method for AWMR, in the future, it can be applied to produce an AWMR platform for multipurpose. This research was conducted in two stages of development. The first year is the research that is currently being carried out, focused on sensor modeling, designing SLAM-based navigation models, and making navigation system testbeds. This research produces a trajectory navigation and control system that can be implemented on an AWMR platform for the purposes of logistics, transportation, and patient waste in hospitals.
Volume: 14
Issue: 3
Page: 322-331
Publish at: 2025-09-01

Robot Gaussian-historical relocalization: inertial measurement unit-LiDAR likelihood field matching

10.11591/ijra.v14i3.pp438-450
Ye-Ming Shen , Min Kang , Jia-Qiang Yang , Zhong-Hou Cai
Robot localization is a foundational technology for autonomous navigation, enabling task execution and adaptation to dynamic environments. However, failure to return to the correct pose after power loss or sudden displacement (the “kidnapping” problem) can lead to critical system failures. Existing methods often suffer from slow relocalization, high computational cost, and poor robustness to dynamic obstacles. We propose a novel inertial measurement unit (IMU)-LiDAR fusion relocalization framework based on Gaussian historical constraints and adaptive likelihood field matching. By incorporating IMU-derived yaw constraints and modeling historical poses within a 3σ Gaussian region, our method effectively narrows the LiDAR search space. Curvature and normal vector-based feature extraction reduces point cloud volume by 50–70%, while dynamic obstacle filtering via multi-frame differencing and neighborhood validation enhances robustness. An adaptive spiral search strategy further refines pose estimation. Compared to ORB-SLAM3 and adaptive Monte Carlo localization (AMCL), our method maintains comparable accuracy while significantly reducing relocalization time and CPU usage. Experimental results show a relocalization success rate of 84%, average time of 1.68 seconds, and CPU usage of 38.4%, demonstrating high efficiency and robustness in dynamic environments.
Volume: 14
Issue: 3
Page: 438-450
Publish at: 2025-09-01

An Internet of Things based mobile-controlled robot with emergency parking system

10.11591/ijra.v14i3.pp370-380
Abdul Kareem , Varuna Kumara , Vishwanath Madhava Shervegar , Karthik S. Shetty , Manvith Devadig , Mahammad Shamma , Kiran Maheshappa
This paper presents an Internet of Things (IoT) based mobile-controlled car with an emergency parking system that integrates advanced functionalities to enhance safety and user convenience, utilizing the ESP32 microcontroller as its core. The system allows users to control the car remotely via a mobile application, leveraging Wi-Fi connectivity for seamless communication. Key features include LED indicators for various operations such as reversing, left and right turns, and brake activation, ensuring clear signaling in real-time. The innovative emergency parking system detects obstacles or emergencies using sensors and halts the vehicle automatically, reducing the risk of accidents. The car's lightweight, energy-efficient design, combined with the versatility of the ESP32, ensures a responsive and reliable operation. Additionally, the system provides an intuitive user interface through the mobile app, enabling precise control and real-time feedback. The proposed system is faster in response compared to the existing systems. Moreover, the proposed system consumes less energy, and hence, it uses the battery more efficiently, extending the time of operation. Lower power consumption ensures longer operation time, reducing the need for frequent charging and making the system more practical. This paper demonstrates the integration of IoT and embedded systems to create a smart vehicle solution suitable for various applications, including robotics, automation, and personal transport. Its cost-effectiveness and scalability make it a viable choice for both hobbyists and developers.
Volume: 14
Issue: 3
Page: 370-380
Publish at: 2025-09-01

Factors impacting high-level mobility in traumatic brain injury: a scoping review

10.11591/ijphs.v14i3.25261
Syazlin Azmi , Nor Azlin Mohd Nordin , Alia Alghwiri , Haidzir Manaf
High-level mobility is crucial for improving quality of life and ensuring active participation in daily routines and community engagement. Therefore, this scoping review explored the available evidence on factors impacting high-level mobility among traumatic brain injury (TBI) individuals and the outcome measures used to evaluate high-level mobility. Following the preferred reporting items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines, five databases were searched: Scopus, Web of Science, Cochrane Library, Science Direct, and PubMed, yielding 109 articles, with eight meeting eligibility criteria. The keywords used in the search strategies were: traumatic brain injury, TBI, brain trauma, traumatic encephalopathy, and high-level mobility. This review revealed that the High-Level Mobility Assessment Tool (HiMAT) was identified as the most commonly used outcome measure for assessing high-level mobility. The key factors that may influence the outcome of high level mobility in people with TBI are age, sex, mechanism of injury, duration of post-traumatic amnesia, and individual endurance. The associations between individuals’ factors and outcomes in TBI studies exhibit significant variation. This can be attributed to several factors, including the diverse characteristics of TBI samples, different neurological recovery rates, methodological differences, timing of assessments, interactions between factors, and potential moderators.
Volume: 14
Issue: 3
Page: 1189-1200
Publish at: 2025-09-01

Depression and cognitive impairment in Malaysian elderly: insights from a nationwide study

10.11591/ijphs.v14i3.25220
Azlina Wati Nikmat , Nor Jannah Nasution Raduan , Nurul Azreen Hashim , Noor Azleen Ahmad Tarmizi , Nor Anita Affandi , Nor Farahdila Hairoman , Muhd Zulfadli Hafiz Ismail , Tengku Mohd Saifuddin Tengku Kamarulbahri
Depression and cognitive impairment are two prevalent mental health conditions among older adults. This study aimed to investigate the factors associated with cognitive impairment among older adults with depression in Malaysia. Data were drawn from the National Health and Morbidity Survey 2018, a nationwide, cross-sectional study using a two-stage stratified cluster sampling. The sample included respondents aged 50 years and above. Cognitive impairment was assessed using the identification and intervention for dementia in the elderly (IDEA) screening tool, while depression was identified using the validated Malay version of the Geriatric Depression Scale (M-GDS-14). Key variables examined included sociodemographic characteristics, physical activity levels, and social support. Bivariate and multiple logistic regression analyses were performed to identify factors significantly associated with cognitive impairment. Results indicated that cognitive impairment was significantly higher among physically inactive individuals (AOR = 2.70, 95% CI: 0.21, 0.65) and those with low to fair social support (AOR = 1.79, 95% CI: 1.12, 2.86). These findings highlight the importance of incorporating physical and social activities into care plans for elderly patients with depression, particularly those with cognitive impairments.
Volume: 14
Issue: 3
Page: 1129-1136
Publish at: 2025-09-01
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