Journal of Advanced Industrial Technology and Application
The Journal of Advanced Industrial Technology and Application (JAITA) is a new international peer reviewed open-access multidisciplinary journal encompassing a broad spectrum of themes in industrial engineering technology and application. JAITA is aiming to revolutionize industry by promoting innovative and effective research. JAITA welcome original research articles/manuscripts as long as their research questions are important, new, and relevant to readers or their designs are appropriate and robust. Journal publication frequency is twice a year (June and December).
An Integrated IoT-Based Smart Home System for Safety and Automation
This paper presents the design and implementation of a unified smart home system that combines facial recognition for access control, hazardous gas detection, and IoT-based appliance automation. The system employs an ESP32-S3 CAM microcontroller with a pre-trained DeepStack model for real-time facial identification, MQ-series gas sensors for gas detection, and a mobile application developed using MIT App Inventor for remote control of appliances. Google Sheets functions as a lightweight cloud backend for data logging and system monitoring. Experimental results confirmed the system’s high reliability under various lighting conditions, sub-second switching latency for appliances, and reliable gas detection at multiple distances. The results demonstrate that the proposed system provides a low-cost, modular, and scalable framework suitable for enhancing residential safety and convenience.
Department of Electrical and Electronic Engineering
Copyright (c) 2026 Journal of Advanced Industrial Technology and Application https://creativecommons.org/licenses/by-nc-sa/4.0
Indoor Air Quality Index–Based Assessment and Improvement Strategies for Selected Kindergarten Classrooms in Pagoh, Johor
Indoor air quality (IAQ) in kindergarten classrooms is critical due to children’s vulnerability to environmental pollutants and thermal discomfort. This study assessed IAQ conditions and determined the Indoor Air Quality Index (IAQI) status of two private kindergartens in Pagoh, Johor namely S1 and S2, using a quantitative field measurement–based approach. Temperature, relative humidity, CO?, TVOC, PM?.?, and PM?? were monitored over two school days and evaluated against Department of Occupational Safety and Health (DOSH) and Singapore Standard (SS 554) guidelines, and IAQI values were calculated using linear interpolation, where the lowest IAQI value represented the overall indoor air quality status. The results showed that chemical pollutants generally complied with the recommended limits; however, dominant parameters affecting IAQ differed between the two kindergartens. S1 was classified as Unhealthy due to elevated temperature (34.5?) and RH (87%), with IAQI values of 39.1 and 42.7, respectively. In contrast, S2 was classified as Hazardous due to high CO? concentrations (2755 ppm) associated with limited ventilation which recorded a critically low IAQI value of 9.0. These findings highlight the need for improved ventilation and thermal management in kindergarten classrooms.
Carbonised Agro-Waste Adsorbents for Automotive Lubricating Oil Removal
The increasing generation of waste lubricating oil, driven by expanding industrial and automotive activity, poses a significant threat to aquatic ecosystems due to its persistence, hydrophobicity, and complex chemical composition. This study evaluates two abundant agro-waste residues: rice husk (RH) and sugarcane bagasse (SB) as potential adsorbents for lubricating oil removal. Both biomasses were pre-treated with 0.1 M NaOH to enhance surface porosity and hydrophobicity, followed by carbonisation at 550 °C. Three adsorbent formulations were prepared based on RH:SB weight ratios of 24:6, 15:15, and 6:24 g. Batch experiments were conducted at oil concentration of 25, 30, and 35 v/v% and contact times of 10, 20, and 30 min using a fixed 30g adsorbent dosage of RH and SB. The response behaviour was further examined using ANOVA and contour-plot analysis under Response Surface Methodology to interpret factor interactions and adsorption trends. All adsorbent mixtures demonstrated high removal efficiencies, achieving up to 100% oil removal, with the 15:15 g ratio showing the most consistent performance at 20 v/v% of oil concentration. FTIR analysis confirmed key lignocellulosic functional groups such as hydroxyl, carbonyl, methylene, aromatic structures which supporting the strong intermolecular interactions responsible for oil removal. Overall, the findings demonstrate that carbonised RH and SB are viable, low-cost, and environmentally sustainable adsorbents capable of efficiently removing used lubricating oil.
Copyright (c) 2025 Journal of Advanced Industrial Technology and Application https://creativecommons.org/licenses/by-nc-sa/4.0
Evaluation of Thermal, Acoustic, and Physical Properties of Bamboo Ceiling Panels Made from Three Species
Bamboo has gained attention as a sustainable alternative to conventional ceiling materials, which often suffer from issues such as poor moisture resistance and limited durability. This study evaluates the thermal, acoustic, and physical properties of ceiling panels produced from three bamboo species which are Gigantochloa scortechinii, Dendrocalamus asper, and Gigantochloa levis, bonded with phenol formaldehyde. The panels were fabricated in strip form and tested for density, thermal conductivity, water absorption, and sound absorption using standard laboratory methods. Results show that Dendrocalamus asper exhibited the best overall performance, achieving the lowest thermal conductivity (0.043 W/m·°C) and the highest sound absorption coefficient at high frequencies (1.311 at 4000 Hz). These findings demonstrate that bamboo-based ceiling panels, particularly those made from Dendrocalamus asper, offer strong potential as energy-efficient and acoustically effective alternatives to gypsum ceilings.
Development of IoT Monitoring with Solar Tracking System for Multi-Purpose Building
This paper discusses the development of an Internet of Things (IoT)-based solar tracking and monitoring system designed to enhance energy efficiency in multipurpose buildings. To optimize solar energy absorption throughout the day, a photovoltaic panel is integrated with a dual-axis solar tracking system. Real-time data, such as voltage, current, and light intensity, is collected and transmitted by an ESP32 microcontroller to a cloud-based platform for remote monitoring and analysis. When compared to a fixed solar panel, a prototype system created and tested under various conditions demonstrated improved energy output. The findings demonstrate that the system facilitates sustainable energy management in building applications, enhances solar efficiency, and reduces the need for human monitoring.
IoT, Solar tracking system, Dual-axis tracker, Renewable energy, ESP32, Energy monitoring, Sustainable buildings
A Review of Emerging Technologies in Robotic Arm for Sorting Applications
In recent times, the growing complexity and scale of manufacturing operations have necessitated the need for a robust material handling system. One of the most important revolutions in this area is the application of a robotic arm to sorting operations. This review provides an overview of the advances in robotic sorting systems, outlining the interactions among component parts. More than 50 peer-reviewed journal articles from 2015 to 2025 were considered for the analysis. Statistical findings show that 4-dof robotic arms dominate the literature with 32%, while Arduino microcontrollers and color as a sorting criterion remain the most widely adopted with 69% and 51% respectively, due to their affordability and ease of use. The survey classifies the present robotic technologies according to a three-level taxonomy: perception, decision, and execution, while stressing the interdependency of this framework. Furthermore, the review recommends the application of reconfigurability, artificial intelligence (AI), and multimodal sensing technologies to existing robotic sorting systems as a means of increasing intelligence and the flexibility of future robotic sorting systems.
Addressing Supply Chain Inefficiencies in Nigeria Manufacturing: A Blockchain-Enabled Frameworks for Enhanced Visibility and Traceability
This paper assesses the performance implication of blockchain implementation in manufacturing supply chains in South-West Nigeria through a quasi-experimental, pre-post, and mixed-methods study. The data on the quantitative key performance indicator (KPI) of 150 manufacturing companies and the qualitative data of 100 top executives were examined. The results suggest that, the use of blockchain has a high level of traceability (up to 95%), reduced fraud (?90%), and cost effectiveness (?70%). Though, the results shows positive performance improvement, but the issues related to the initial investment, system interoperability, lack of scalability, and regulatory uncertainty still exist. The paper suggests a blockchain-based supply chain system that connects the technological elements and quantifiable performance indicators which can provide useful evidence-based advice to policy-makers and industry stakeholders.
Research Trend in Coastal Sediment Transport Using Numerical and Empirical Models
Coastal sediment transport remains a critical research domain due to its implications for shoreline stability, erosion management, and sustainable coastal development. Despite extensive studies, challenges persist in integrating numerical and empirical models to capture the complex dynamics of sediment movement under varying hydrodynamic conditions. This study addresses the research gap by conducting a bibliometric analysis of global scientific literature on coastal sediment transport using numerical and empirical approaches. Data were retrieved from the Scopus database through advanced search techniques, yielding 1,089 publications. The dataset was first processed using OpenRefine to clean and harmonize author names, keywords, and affiliations, ensuring accuracy and consistency. Statistical trends, including annual publication growth, prolific authors, contributing journals, and leading countries, were examined through the Scopus analyzer. Furthermore, visualization of research networks such as co-authorship, keyword co-occurrence, and citation patterns was performed using VOSviewer, offering insights into the structural relationships within the field. Results reveal a steady increase in publications over the last two decades, with the United States, China, and the United Kingdom emerging as central contributors through high productivity and extensive collaboration networks. Frequently occurring keywords highlight a strong focus on sediment transport modeling, shoreline evolution, and climate change-driven coastal dynamics. The visualization further identifies clusters of international collaboration and thematic research streams, reflecting the interdisciplinary nature of the field. Overall, this bibliometric study provides a comprehensive overview of research trends, key contributors, and collaborative structures in coastal sediment transport, emphasizing the pivotal role of numerical and empirical modeling. The findings not only map the knowledge structure but also suggest future research directions to strengthen predictive capabilities and inform sustainable coastal management practices.
Thermo-Mechanical Behaviour of Schizostachyum Grande Bamboo Fibre, Epoxy and Vinyl Resin Thermoset for Potential in Composite Application
This study was conducted to investigate bamboo fibre and thermoset resin’s thermophology and thermoset resin for composite applications and to delve into the morphology, behaviour, and mechanical properties of bamboo fibres from the species Schizostachyum grande, as well as thermoset resins such as vinyl and epoxy. Besides, fibre and thermoset resins were incorporated to achieve the desired mechanical properties, specifically for tensile strength and elongation characteristics. Additionally, this study was also conducted to determine physical and chemical composition properties, where Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray (EDX) tests were executed on bamboo fibre and epoxy and vinyl resins. Furthermore, Thermogravimetric Analysis (TGA) and Fourier Transform Infrared Spectroscopy (FTIR) tests were performed to determine the physical performance of the material in terms of mass loss over time. The data obtained for bamboo fibre, epoxy, and vinyl resin were then compared for the factors of maximum stress, stiffness, deflection, and maximum load. Hence, this research contributes to the understanding of bamboo fibres and thermoset suitability for sustainable engineering applications by providing comprehensive data on morphology, behavior, and tensile properties. The results of this research are useful in terms of design and materials selection processes, enabling the creation of more robust and ecologically friendly engineering solutions for the chosen fibre and thermoset resin towards sustainable structures, such as modular houses.
Evaluating Indoor Lighting Performance: A Comparative Study Using Dual Methods for Different Colour Schemes
Efficient lighting design is fundamental to creating comfortable, safe, and functional indoor workplace environments. An optimal lighting system not only ensures adequate illumination for visual tasks but also enhances occupant safety and visual comfort. In Malaysia, adhering to standard lighting recommendations is crucial and requires careful consideration of design elements, specifically the interaction between light sources and room surface colours. However, previous studies have largely focused on the efficacy of light sources in isolation, often overlooking the combined influence of light source type and room colour on illuminance distribution (lx). This study aims to bridge this gap by investigating the effects of different wall and floor colour schemes on light distribution using two distinct light source types. The methodology employs a dual approach: experimental testing via goniophotometer measurements and photometric simulation using DIALux software to ensure accurate illuminance results. The findings demonstrate that white colour schemes consistently yield significantly higher average lux values across both light source types compared to darker schemes. These results underscore the critical importance of integrating surface colour selection into lighting design strategies to maximize energy efficiency and visual performance in building interiors.
Light source; Goniophotometer; DIAlux software and distribution light (lux)
Egg Defects Detection Using Bidirectional Long Short-Term Memory Network
Eggs are a vital nutritional resource globally, making their inspection crucial for maintaining quality and ensuring food safety. Motivated by this need, a machine vision system incorporating deep learning techniques was developed to detect egg defects. The machine vision system has a rotating mechanism that allows for comprehensive visualization of the egg surface from various angles, leading to a more accurate assessment. The proposed system leverages deep feature extraction using a pre-trained convolutional neural network and analyses these features with a Bidirectional Long Short-Term Memory (BiLSTM) network. The types of egg defects that this study aimed to detect were bloodstained, cracked and dirty eggs. A total of 400 eggs sample were used with 6 images per egg resulting with a dataset of 2400 images for the proposed deep learning method. The performance evaluation of the model revealed an accuracy of 97.71% in detecting egg defects, with a recall score of 0.9788, a specificity score of 0.9926, a precision score of 0.9770, and a F1 score of 0.9770. Comparisons with other state-of-the-art deep learning and machine learning methods like (SVM, VGG16, YOLOv5) indicate that the proposed model has certain advantages and does not differ much in terms of accuracy for defect detection. The result from this study demonstrates the potential of sequential feature modelling for robust egg defect detection.
Eggs Defect, deep learning, Bidirectional Long Short-Term Memory (BiLSTM)
The Application of Machine Learning and Reliability Block Diagram (RBD) in Prognostic Health Management (PHM) for Pumps
This study proposes an integrated Prognostics and Health Management (PHM) framework for centrifugal pumps by combining performance data (vibration, temperature, pressure) and functional failure data using Artificial Neural Networks (ANN) and Reliability Block Diagram (RBD). The dataset obtained from operational operating plant reports was preprocessed using PCA and SMOTE to address dimensionally and class imbalance. A NAR-based ANN model was developed to predict time-to-failure and the predicted outputs were integrated into an RBD model for availability estimation. The model achieved an MSE of 0.124 and high correlation with observed degradation trends. The RBD analysis revealed an estimated system availability of 34%, indicating significant downtime and the need for reliability improvement strategies. The proposed hybrid PHM framework demonstrates potential for early degradation detection and maintenance optimization in rotating machinery.
Prognostic Health Management, Reliability, Availability, Maintainability, Time to failure, Pump
Comparative Study of Commercial and Plastic Waste Resins for Groundwater Treatment
Groundwater contamination by organic and inorganic pollutants poses serious health and environmental concerns. Conventional resins are effective but costly. There is a need for low-cost, eco-friendly alternatives, particularly through plastic waste valorization. This study compares the performance of commercial and plastic waste resins for groundwater treatment. Scanning electron microscopy analysis revealed that the commercial resin had a smooth, porous structure, while the plastic waste resin showed a rough, irregular surface. Energy dispersive X-ray and Fourier transform infrared spectroscopy analysis confirmed key ion exchange functional groups, including sulfonic acid, in the commercial resin. X-ray diffraction analysis showed the commercial resin was amorphous with low crystallinity. Results showed that the commercial resin outperformed the plastic waste resin by removing 98.6% biochemical oxygen demand (BOD), 85% chemical oxygen demand (COD), 88.9% total suspended solids (TSS), 50% total dissolved solids (TDS), and 66% iron. The plastic waste resin achieved lower removal rates of 66.7% TSS, 25% TDS, and 19.2% COD. In column method, the commercial resin removed 91.65% total hardness within 4 hours at 2163 cm³ dosage, while the plastic waste resin achieved up to 52.12%. The superior performance is linked to the commercial resin’s favorable structure and functional groups for ion exchange. The use of plastic waste resin as a potential ion exchange material for water treatment supports waste valorization and aligns with circular economy principles. However, its performance requires further optimization, which can be pursued through strategic collaboration with water treatment industries.
Ion exchange resins, commercial, plastic waste, groundwater
Performance Metrics of Different Machine Learning Models for Windows Malware Detection
This study experimentally evaluates and analyzes the performance of various machine learning models for Windows malware detection. Their metrics are further analyzed to identify the most effective approach. For this purpose, the researchers employed a diverse dataset to train and assess the models. The used dataset contains known Windows malware samples and benign files. Besdies, the chosen machine learning algorithms, such as Logistic Regression (LR), AdaBoost, LightGBM (LGBM), XGBoost (XGB), Decision Trees (DT), Gradient Boosting, Bagging, Random Forest (RF), and Support Vector Machines (SVM), have various techniques. The study focuses on key performance metrics: Accuracy, Precision, Recall, F1 Score, Specificity, False Positive Rate (FPR), Negative Predictive Value (NPV), False Negative Rate (FNR), and Error Rate. They are used to thoroughly assess the models' effectiveness in distinguishing between malware and benign samples. Additionally, the exploration of the impact of feature selection and extraction methods on model performance is carried out to gain better insights. The study results demonstrate variations in the models' effectiveness. It is noted that certain algorithms demonstrate superior performance in specific metrics. They also offer significant perspectives into the strengths and weaknesses of various machine learning models in the detection of Windows malware, contributing valuable knowledge to the development of more robust cybersecurity strategies. The study implications can hopefully be used to develop an effective and accurate malware detection model. It is expected the model may ultimately foster the security of Windows environments.
Optimized Factory Layout Design for Enhanced Productivity and Quality: A Case Study on Aerokit Painting
In automotive production, the improvement in production effectiveness and quality while containing costs is essential. This research examines the painting process in an automotive plant in Malaysia that suffered from low throughput rates, high defect levels, and an overworked quality control section. To remedy these issues, the layout of the factory was transformed into a U-shaped layout incorporating Lean Manufacturing values, Statistical Process Control (SPC), and real-time Power BI monitoring. The interventions improved the flow of material, decreased operator walking distances, and added in-process quality checks in addition to operator self-audits. Installation of these measures yielded a 33% increase in production volume, an 80% defect per vehicle reduction (DPV), and a 47% reduction in takt time. The results show the effectiveness in combining Lean values with digital monitoring and offer a real-world model for the enhancement of quality and productivity in automotive painting operations.
Investigation of Viscosity Effects on Flow Rate and Pressure Drop in a PVC Fluid Transfer System Using Different Water Sources
Fluid transfer systems are essential in domestic and industrial settings, requiring efficient design for fluid conveyance. This study developed a fluid transfer system with centrifugal pumps, gate valves, and PVC plumbing, ensuring structural stability with a metal frame weighing 28.9 kg and tank guides weighing 67.7 N and 47.6 N. Flow analysis showed turbulent conditions with a Reynolds number of 9160. Pressure drops were highest in the longest pipeline (0.171 N/m³) and significant at 90° elbows (0.1174 N/m³), compared to gate valves (0.0214 N/m³). Tests with rainwater, tap water, and stream water indicated rainwater had the highest flow volume (48.65 L in 20 min) and flow rate (2.43 L/min), while tap and stream water had lower rates (2.07 and 1.83 L/min). The experimental results confirms established fluid dynamics principles that higher viscosity fluids flow more slowly through pipes, substantiating the dependence of flow rate on fluid viscosity.
Design Enhancement of Hose Rolling Tool for Firefighters Using DFMA
Firefighting operations depend significantly on effective equipment, with hose rolling tools being crucial for the swift deployment and recovery of fire hoses. Existing hose roller designs frequently exhibit significant component counts, intricate assembly, and elevated manufacturing costs, which hinder operational efficiency and escalate manufacture expenses. This project seeks to improve the design of a hose rolling tool for firefighters by utilizing Design for Manufacturing and Assembly (DFMA) principles to decrease part complexity and cost. The project entailed evaluating the current hose roller design, highlighting inefficiencies, and methodically improving the tool through SolidWorks modelling and manual Design for Assembly (DFA) analysis. Comparative evaluations were performed to analyze part quantity, material expenses, and assembly durations between the original and revised models. The findings indicated a substantial decrease in total components (from 40 to 25), an 11% reduction in production expenses, and a 48% enhancement in assembly efficiency. These findings underscore the efficacy of DFMA in enhancing product design for manufacturing and assembly, resulting in more economical and user-centric firefighting equipment. In summary, the implementation of DFMA principles significantly enhanced the manufacturability and operational efficacy of the hose rolling tool, offering a viable framework for future advancements in firefighting equipment.
Anthropometric Assessment for Ergonomic School Furniture Design to Prevent Student Discomfort and Musculoskeletal Disorders
Classroom furniture plays a critical role in shaping the comfort, posture, and academic performance of students. However, a widespread mismatch between school furniture dimensions and students’ anthropometric characteristics often results in discomfort and musculoskeletal disorders (MSDs). This study aims to assess the anthropometric measurements of primary and secondary school students in Osun State, Nigeria, to recommend ergonomically appropriate classroom furniture dimensions. Anthropometric data were collected from 900 students (124 in primary and 776 in secondary schools), equally divided by gender and ranging in age from 6 to 20 years. Measurements included sitting height, elbow height, shoulder height, popliteal height, buttock-popliteal length, and other key dimensions, using a standard anthropometer. Existing classroom furniture dimensions were also recorded. Using Microsoft Excel 365, percentiles (5th, 50th, and 95th) were computed to determine appropriate design values. The analysis revealed significant mismatches between current furniture and students' body dimensions, contributing to poor posture and discomfort. Design recommendations were developed for seat and desk dimensions tailored to both primary and secondary students. For instance, the ideal seat height is 28.35 cm for primary and 37.55 cm for secondary students, while desk surface heights range from 42.80–45.61 cm and 50.73–54.87 cm, respectively. The study concludes that incorporating anthropometric data into classroom furniture design can significantly reduce student discomfort and prevent long-term musculoskeletal issues. It emphasizes the urgent need for region-specific ergonomic standards to ensure student well-being and enhance academic productivity.
Review Study of Non-Forced Convection Heat Transfer Inside Enclosures with Different Enhancement Techniques and Configurations
Many industrial engineering applications such as thermal storage plants, solar energy, cooling in reactors, microelectronic electrical systems, and gas-insulated electrical systems use natural convection heat transfer represented by the principle of heat transfer from the heating source to the cold ambient or cold cavity wall. The function of the outer surface of the cavity is to protect the body inside the cavity in the harsh external environment by also reducing the heat transfer process from the hot inner surface. On this topic, many researchers conducted their previous studies and literary investigations using various methods to enhance heat transfer by natural convection, such as mixing nanomaterials with water or inserting porous materials into various configurations to increase the coefficient of thermal conductivity of the main working fluid. Other methods have been applied, for example, vibration, Rayleigh numbers, boundary conditions, magnetic field, or changing the geometry of the cavity composition. The current research aims to study heat transfer by natural convection inside cavities of various configurations, including square, non-square, triangle, and rectangle, in addition to addressing ways to enhance heat transfer, the most important nanofluid and porous medium.
Assessment of a Safe Work-Impulse for Farmers: A Case Study of Ilara-Mokin, Ondo State, Nigeria
The study measured the heart rates of farmers in Ilara-mokin while they carried out a few regular farm tasks with a view to create a safe work-impulse chart for farmers in that locality. This is expected to provide the information required for the adequate use of muscular force and the prevention of fatigue or physical exertion, during farming. Farmers who were available and were willing to participate in the study were divided into five age groups, such as below 25, 25-34, 35-44, 45-54, and above 54 years, and their heart rates were monitored and recorded under three different categories of farm activities or load (light load, medium load, and heavy load) using a premium pressure monitor with comfit cuff. The time and the heart rate at which the farmers feel a sense of discomfort or tiredness were used to evaluate the safe work-impulse for each category of activities. The result shows that farmers below 45 years of age record a work-impulse of about 9.0M kNs and 7.2H kNs for medium and heavy loads respectively while older farmers manage to sustain medium and heavy loads at a work-impulse of 7.2M kNs, 5.4M kNs and 9.0M kNs, 5.4M kNs respectively. In conclusion, the study revealed that while farmers of any age can handle a light activity for a longer period of time than 18 minutes, they may not be able to sustain heavier loads for a longer period.
Design and Fabrication of an Innovative Rattan Splitting Machine for Efficient and Sustainable Production of High-Quality Rattan Material
This research was conducted to address the limitations of the traditional rattan splitting process, which had been time-consuming, labour-intensive, and heavily reliant on manual labour to produce thin strips for furniture and handicrafts. To improve productivity and alleviate physical strain on workers, a fully mechanical rattan splitting machine was developed and tested, purposely designed without modern technology that could be unfamiliar to the labour force. The machine was built with a durable blade system that precisely split rattan into thin, uniform strips, ensuring consistent, and high-quality results. Its compact and adaptable design included adjustable settings to accommodate different rattan sizes and thicknesses, powered by electricity for straightforward operation and maintenance. Research involved meticulous engineering design, material selection, prototype construction, and performance testing to measure efficiency, precision, and consistency in output quality. Key findings revealed significant reductions in manual labour requirements, increased production speed, and uniform quality in processed rattan strips. These results indicated that the machine had greatly enhanced productivity within the rattan industry, enabling larger-scale production with consistent quality. In conclusion, the mechanical rattan splitting machine provided a practical and efficient solution for the industry, transforming a labour-intensive process into a streamlined operation that increased productivity, lowered labour costs, and maintained product standards. This development represents a significant advancement for the rattan industry, offering a sustainable solution that meets the current capabilities of the workforce while supporting industry growth and modernization.
Mechanical Engineering, Renewable Energy, Industrial Engineering
Utilizing Calcined Hard Clam Shells for Phosphate Removal Using an Up-flow Column Reactor Through Water Solution
Phosphate pollution in aquatic environments is a critical environmental issue that poses a significant threat to water quality and the ecosystem, primarily from agricultural runoff, industrial discharges, and domestic wastewater effluents. This research aims to evaluate the effectiveness of calcining hard clam shells in phosphate removal and to understand the mass transfer process within an up-flow column reactor. Experimental data was analyzed using an up-flow column reactor to study the adsorption of phosphate deposited on the surface of calcined hard clam shells. According to preliminary findings, calcined hard clam shells show great potential for use as phosphate adsorbents due to their promising capacity and efficiency. The primary materials responsible for phosphate removal are calcium oxide (CaO) and calcium carbonate (CaCO?) generated through the calcination process, facilitating phosphate adsorption and precipitation. The analysis indicates that deeper adsorbent layers sustain better removal efficiencies throughout time. In contrast, shallower adsorbent layers approach solute saturation quickly through an up-flow column reactor. More extended periods of effective adsorption are provided by deeper adsorbent beds, according to the Bed Depth Service Time (BDST) model. These results are corroborated by the Thomas and Modified Mass Transfer Factor (MMTF) models, which demonstrate that while adsorption rates are higher in shallower beds, deeper beds have higher total capacities and longer service durations. This study contributes a thorough assessment of calcine hard clam shells as an affordable and environmentally friendly way to remove phosphate from wastewater, helping to reduce eutrophication in aquatic environments and improving tertiary wastewater treatment methods.
Ultrasonication-Assisted Preparation of Virgin Coconut Oil-Kelulut Honey-Vitamin E Emulsion and Its Bioactivity for Lip Balm Application
The growing demand for natural and eco-friendly skincare products has spurred innovation in cosmeceutical formulations, including lip balms. This study developed an emulsion-based lip balm incorporating Virgin Coconut Oil, Kelulut honey, and vitamin E, utilizing ultrasonication to enhance stability and bioactivity. The moisturizing, antibacterial, and antioxidant properties of these ingredients were combined with surfactants (Tween 20, soy lecithin, or a 50:50 blend) and processed through ultrasonication and/or homogenization. Bioactivity was assessed using pH, Total Phenolic Content (TPC), Total Flavonoid Content (TFC), 2,2-Diphenyl-1-Picrylhydrazyl (DPPH), and Ferric Reducing Antioxidant Power (FRAP) assays. Sample F (50:50 blend with ultrasonication) demonstrated the highest TPC (38.95 µg GAE/mL), TFC (5.59 µg QE/mL), DPPH inhibition (17.14%), and FRAP activity (2.68 µg GAE/mL), with a skin-compatible pH (4.80–5.50). The storage stability test conducted at 4°C for one week revealed visible phase separation in all samples, with samples B, D, and F (with ultrasonication) demonstrating comparatively less separation than their respective counterparts A, C, and E, (homogenization only) indicating enhanced emulsion stability under chilled conditions. Sensory evaluation identified Sample F as the most preferred, excelling in texture, spreadability, and absorption. This study underscores the significance of ultrasonication, surfactant synergy, and ingredient selection in developing sustainable, high-performance cosmeceutical formulations.
Assessing the Environmental Impact of Bubble Wrap: A Life Cycle Assessment using LCA FE Software
Packaging plays a key role in protecting goods, especially in e-commerce and logistics, where bubble wraps are valued for their lightweight and durable nature. However, its widespread use raises environmental concerns, including resource depletion and waste. This study explores the sustainability of remanufacturing secondary packaging, specifically bubble wrap, using a Life Cycle Assessment (LCA) approach via LCA for Experts (LCA FE) software. The assessment covers the full life cycle of single-layer LLDPE bubble wrap—from raw material extraction and manufacturing (extrusion, bubble formation, cooling, cutting) to end-of-life disposal. The LCA tracks energy use, materials, and environmental impacts to identify hotspots. Results show fossil resource depletion (ADP Fossil) is the dominant impact, accounting for 95.47%, mainly due to LLDPE production. Other notable impacts include global warming potential and freshwater aquatic ecotoxicity, largely driven by manufacturing energy use, while transport and disposal have minor effects. The study highlights the need for more sustainable packaging through biodegradable materials, better recycling, and circular economy principles to reduce environmental impact.
Development of a Mobile Application for Building Maintenance by Implementing Augmented Reality Technology
Building maintenance procedures are currently inefficient, which emphasizes the need for more creative and efficient solutions. In order to improve maintenance operations, the present study aims to develop a functional testing of a mobile application that combines Building Information Modelling (BIM) and Augmented Reality (AR). The development process was tested using Autodesk Revit to produce 3D models that included comprehensive equipment and building material specifications. Subsequently, the AR component of the application was developed using Unity Hub in conjunction with the Vuforia Software Development Kit (SDK). Alpha and Beta testing were deployed and tested in Android devices comprising two key phases. The application showed 100% operational stability with all features functioning as intended throughout alpha testing, which comprised internal evaluations to confirm functionality, stability, and usability. The System Usability Scale (SUS), which consists of 10 Likert-scale questions assessing user confidence, ease of interaction, and perceived usefulness, was used in beta testing to gather end-user input. Beta testing confirmed the system’s effectiveness, with an average SUS score of 72.5 and 90% of users reporting that the application is easy to learn and use. The study demonstrates that integrating AR with BIM in a mobile application fundamentally enhances building maintenance by streamlining processes. This study offers a solid foundation for further research and development and shows how combining AR and BIM might enhance conventional building maintenance.
Characterization of Clays from Adamawa State, Nigeria, for 3D Printing Applications
The Sustainable Development Goal 6 aims to ensure availability and management of sustainable water and sanitation, and this is particularly poignant for rural communities that rely heavily on sources such as streams, rivers, hand dug wells and in rare cases boreholes. In Nigeria, only a fraction of the population use improved drinking water sources and sanitation facilities. This makes access to safe and clean drinking-water in the rural areas of Nigeria practically impossible, leading to several health complications. This plays a significant role in diarrhoea related cases in Nigeria, in both adults and children. This research assessed the viability of locally sourced clay from Adamawa State as candidate material for 3D ceramic printed water filter. The assessment involves testing the physical, microstructural and mineralogical properties of the local materials obtained from different areas of the State. A prototype water filer was developed following geometric designs in Autodesk Fusion 360, and trial mix designs of composite materials using 3D printing extrusion process. The result indicates that the clays satisfied minimum plasticity requirements and exhibited satisfactory extrusion property. Heavy metals were not detected in all the clay materials, and composition displayed high amounts of silica and alumina content. The application of 3D printing technology will go a long way towards improving state-of-the-art and refinining the process as well as provide real time opportunity for correcting and editing flaws detected at each stage of prototype development as oppose to the traditional pottery process.
Rain Attenuation Characteristics for Earth-Space Communication in parts of Northeast and Southwest Nigeria
The characteristics of rain attenuation for earth-space communication in three Northeast States (Adamawa, Gombe and Taraba) and three Southwest States (Lagos, Oyo and Ogun) of Nigeria are presented in this paper. 33 years rainfall data obtained from the Nigerian Meteorological Agency (NiMet) was utilised. Chebil rain rate model was used to compute the point rainfall rate, while the ITU-R P.618-12 model was used to compute the rain attenuation for the six locations. The point rainfall rate computed in the Northeast ranged between 90.34 mm/h and 96.2 mm/h, while higher rainfall rates that ranged between 99.7 mm/h and 108.2 mm/h were recorded in the Southwest. Elevation angles of 23°, 42.5° and 55° were considered. The computed rain attenuation for the Northeast States ranged between 10.22 dB and 37.14 dB, while that of the Southwest States ranged between 10.60 dB and 41.00 dB for time percentage exceedance of 0.01 at Ku-band. From the values of the rain attenuation predicted, availability of signal is possible at 42.5° and 55° elevation angles but impossible at 23° elevation angle.
Replacement of Sisal Fiber with Jute Fiber in the Production of Plaster of Paris (POP) Ceiling Boards
Plaster of Paris (POP) ceiling boards production is reported to be too expensive, this hinder affordability especially to low-income earners in Nigeria. It high cost is attributed to importation of its constituent materials (Gypsum cement and Sisal fiber). This study assessed the performance of jute fiber as compare to sisal fiber in POP ceiling production. Sisal fiber is imported and sold at exorbitant price within the country. The materials used in this study includes gypsum cement, sisal and jute fibers. The jute fiber was obtained from jute stalks bought from Girei market in Girei LGA Adamawa State, Nigeria. These stalks were retted using tank retting method, and fibers obtained were chemically modified. Specimens were prepared and tested using standard methods outlined in ASTM C 473 – 07 (2009). Flexural strength, nail pull resistance and water absorption of the specimens were determined. Use of jute fiber as reinforcement in POP ceiling boards was found to enhance flexural strength and nail-pull resistance by 4% and 3% respectively. The water absorption of sisal and jute fibers specimens are 6% and 7% which are all within ASTM C1396M-11 (2004) specified maximum limit. Hence jute fiber is considered a suitable alternative to sisal fiber in POP ceiling production Nigeria.
Head Anthropometric of Malaysian Male Adults Using 3D Scanning
Safety helmets are essential for protecting individuals in high-risk industries such as construction, sports, and manufacturing, where head injuries are common. Despite their importance, poor helmet fit is widespread, primarily due to a lack of consideration for anthropometric diversity, which reduces their effectiveness and compromises safety. Anthropometry, the study of human body measurements, played a critical role in this research. Current helmet designs are predominantly based on Western anthropometric data, which fail to accommodate the unique head shapes of Malaysians. To bridge this gap, the study involved 3D scans of 100 Malaysian male participants at UTHM, capturing key anthropometric dimensions such as head circumference, width, and length. These measurements were taken with and without helmets to thoroughly analyze fit discrepancies. The findings highlighted significant anthropometric variations within the population, revealing that many existing helmets did not provide a proper fit. This study emphasizes the importance of incorporating localized anthropometric data in helmet design, offering a solution that improves comfort, enhances safety, and reduces the likelihood of head injuries.
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MXene-Based Photothermal Fabrics Via Dip-Coating for Solar-Driven Evaporation Of Seawater
Solar-driven interface evaporation (SDIE) is a promising and sustainable seawater desalination approach that can perform long-term application. Unlike conventional desalination method, which does not support in off grid area, SDIE offers a viable solution because of its reliance on solar energy and its simple setup. In this work, a MXene/Polypyrrole (PPy) cotton-based fabric was prepared via a dip-coating method to serve as the SDIE system's solar absorber. The MXene and PPy modification endows the fabric with excellent photothermal ability. The optimal MXene/PPy fabric was determined based on two factors (volume of MXene and PPy) and two responses (surface temperature and coating stability). The optimized MXene/PPY fabric, containing 3 ml of MXene and 100 µl of pyrrole, demonstrated minimal coating leaching of 0.026 grams with the ability to provide surface temperature of 64°C. Outdoor performance testing under sunny day showed an average evaporation rate of 0.041 L/m²·h with low conductivity of 0.347 µS/cm, indicating its effectiveness in desalination applications