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International Journal of Sustainable Engineering Innovations
Published by CV Media Inti Teknologi
ISSN : -     EISSN : 31102182     DOI : https://doi.org/10.58723/ijsei.v2i1.150
Core Subject : Economy, Science, Education, Engineering,
Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering
The International Journal of Sustainable Engineering Innovations (IJSEI) is a leading publication dedicated to the intersection of innovation and sustainability within engineering. The journal serves as a vital platform for academics, researchers, and professionals to share original research, reviews, and case studies that promote more environmentally responsible engineering practices. By focusing on the integration of sustainability across various engineering disciplines, IJSEI aims to contribute to the global effort of building a more resilient and eco-friendly future. The scope of IJSEI covers a wide range of critical topics in sustainable engineering. The journal features research on Renewable Energy Systems, including breakthroughs in solar, wind, and geothermal technologies, as well as advancements in smart grids and energy storage. It also explores Sustainable Materials and Construction, with articles on green building designs, recycled materials, and lifecycle assessments. Other key areas include Waste Management and Resource Recovery, which focuses on circular economy models and waste-to-energy solutions, as well as the Economics and Finance of Sustainable Engineering, which analyzes the financial viability and economic impact of green projects. The journal also addresses the importance of Sustainable Engineering Education, highlighting new curricula and teaching methods to foster the next generation of engineers.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 11 Documents
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A Hybrid Microgrid using A Nodemcu Microcontroller S. Prakash; T. Divya; J. Raji
International Journal of Sustainable Engineering Innovations Vol. 1 No. 1 (2025): International Journal of Sustainable Engineering Innovations (August 2025)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v1i1.1

Abstract

Backgorund of study: Access to reliable electricity remains a major issue in remote, hilly, and island areas where conventional power infrastructure is lacking. These communities often face limited energy options, hindering development and quality of life. Renewable energy, particularly when harnessed in hybrid systems, presents an opportunity for sustainable and decentralized solutions. Aims and scope of paper: This study develops a solar-wind hybrid system with battery storage to deliver clean, reliable power to off-grid areas, focusing on design, conversion, optimization, and real-time monitoring. Methods: The system combines solar and wind energy, stabilizes output with boost-buck converters, converts DC to AC via an inverter, uses ESP32 NodeMCU for real-time monitoring through Blynk, and applies MPPT to maximize energy efficiency. Result: The system successfully delivers a stable power supply in off-grid settings by improving energy harvesting efficiency through the MPPT algorithm. Real-time monitoring enhances user interaction and system management. The combination of solar and wind energy supported by battery storage ensures a continuous and dependable power flow. Conclusion : The study confirms that the hybrid microgrid system developed is an efficient, scalable, and environmentally sustainable solution for communities with limited electricity access. It also demonstrates the potential of such technologies to reduce reliance on fossil fuels while promoting clean energy adoption in underserved areas.
Beetroot Extract as Fluorescence Probes for Copper Ion Detection in Aqueous Solution Ganesan Krishnan; Nurul Badrina Aiman Rashidi; Zakirah Buhari
International Journal of Sustainable Engineering Innovations Vol. 1 No. 1 (2025): International Journal of Sustainable Engineering Innovations (August 2025)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v1i1.3

Abstract

Backgorund of Study: Copper contamination in water poses serious health and environmental risks. Excessive exposure can lead to critical human health issues and is toxic to aquatic organisms. Existing detection techniques are often expensive and complex, highlighting the need for more accessible, eco-friendly alternatives. Aims and Scope of Paper: This study explores betanin from beetroot as a low-cost, eco-friendly fluorescence probe for detecting copper ions, highlighting its sensitivity and potential for environmental and biomedical use. Methods: Beetroot extract was analyzed using UV-Vis, PL, and FTIR spectroscopy to examine changes in betanin’s optical properties in response to different copper ion concentrations. Result: The fluorescence intensity of betanin decreased as copper ion concentration increased. A linear correlation (R² = 0.792) was observed between copper levels and absorbance, and the sensitivity was calculated at –6.21828 × 10⁻⁴ A.U./ppm, demonstrating betanin's strong potential as a copper ion detector. Conclusion: The study confirms betanin from beetroot shows strong potential as a low-cost, eco-friendly copper ion detector, supporting sustainable sensing solutions across various fields.
Grid-Connected PV System with Quasi-Z-Source Inverter And ANFIS MPPT J. Raji; S. Lakshmi; S. Prakash
International Journal of Sustainable Engineering Innovations Vol. 1 No. 1 (2025): International Journal of Sustainable Engineering Innovations (August 2025)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v1i1.4

Abstract

Background of Study: The integration of photovoltaic (PV) systems into the power grid is a key step in the transition toward renewable energy. However, challenges such as inconsistent power output, inefficient energy harvesting, and synchronization with the grid limit their effectiveness. Addressing these issues is crucial for reliable and sustainable solar energy utilization. Aims and Scope of Paper: This study introduces an ANFIS-based MPPT strategy to boost PV efficiency and grid stability, focusing on intelligent control and advanced inverter systems for seamless AC integration. Methods: The system uses an ANFIS-based MPPT to dynamically adjust the DC-DC converter’s duty cycle, integrates a Switched Quasi-Z-Source Inverter (SQZSI) for voltage boosting and reliability, employs a single-phase VSI with LC filters to produce smooth AC output, and applies a PI controller for grid voltage and frequency synchronization. Result: The system demonstrated improved energy harvesting efficiency and grid stability. The ANFIS algorithm enabled accurate and rapid tracking of the maximum power point, while the inverter architecture ensured consistent and high-quality power delivery compatible with grid standards. Coclusion: The combination of ANFIS-based MPPT, SQZSI, and synchronized control provides a reliable and efficient solution for integrating solar energy into the modern power grid. This intelligent, robust system enhances both performance and sustainability in renewable power generation.
Multi-Vector Energy Markets for Resilient Grid-Connected Renewable Networks R. Rajasree; D. Lakshm; K. Stalin; R.Karthick Manoj
International Journal of Sustainable Engineering Innovations Vol. 1 No. 1 (2025): International Journal of Sustainable Engineering Innovations (August 2025)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v1i1.5

Abstract

Background of Study: The transition to renewable energy is becoming more complex with the emergence of multi-vector energy systems that integrate electricity, heat, gas, and transportation networks. Managing these interconnected systems requires advanced market mechanisms that can handle the variability of renewable sources while ensuring efficient and reliable energy distribution. Aims and Scope of Paper: This paper evaluates current renewable energy market protocols and proposes a hybrid model to improve grid reliability, flexibility, and efficiency using optimization and game theory. Methods: The study used optimization and game theory to model energy trading, developed a hybrid market with storage and demand response, and assessed dynamic pricing’s impact on load shifting and prosumer behavior. Result: Simulation outcomes showed that dynamic pricing schemes encourage prosumers to shift loads, leading to higher energy efficiency, reduced supply restrictions, and improved grid stability. The model also improved cost-effective resource management across interconnected energy systems. Conclusion: The study shows that a multi-vector hybrid energy market enhances resilience, flexibility, and sustainability, offering key guidance for energy policy development.
Transport Corridor Planning for Zaria Road using Bus Rapid Transit Approach Abubakar Isyaku Ismail; Isah Musa; Lawan Kamiludeen Abba
International Journal of Sustainable Engineering Innovations Vol. 1 No. 1 (2025): International Journal of Sustainable Engineering Innovations (August 2025)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v1i1.11

Abstract

Background of study: Kano Metropolis is experiencing rapid urban growth, creating an urgent need for a modern and efficient urban transport system. Among its key corridors, Zaria Road has emerged as a promising candidate for development using a Bus Rapid Transit (BRT) model to address the challenges posed by current informal and inefficient transportation modes. Aims and scope of paper: This study assesses the feasibility of BRT implementation on Zaria Road by examining traffic patterns, passenger flow, and key traffic nodes, leading to infrastructure and design recommendations. Methods: A mixed-method approach combined field surveys, traffic and passenger counts, questionnaires, and stakeholder interviews with secondary data from recent literature. The analysis used both descriptive and inferential statistics. Result: Public transport on Zaria Road is largely informal, with 65% of operators unlicensed. Tricycles dominate at 67%, averaging 37,198 daily—far surpassing buses and taxis. Peak hours (5–6 a.m. and 9–10 a.m.) see up to 18,960 passengers, mainly commuting from residential areas to key hubs like motor parks, markets, and hospitals. Conclusion: Zaria Road's 90-meter right of way and high passenger demand make it well-suited for BRT development. A 15.9 km corridor with 54 proposed stops is recommended, supported by public-private partnerships and tricycle restrictions to ensure success.
Evaluation of the Lighting System on Boeing 737-300 Aircraft PT. Mulya Sejahtera Technology Bandung Riadi Parasian Sirait; Catra Indra Cahyadi; Rofi Juliatma; Ayub Wimatra
International Journal of Sustainable Engineering Innovations Vol. 1 No. 1 (2025): International Journal of Sustainable Engineering Innovations (August 2025)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v1i1.60

Abstract

Background of study: Aircraft maintenance is vital for flight safety. To connect theory with practice, students at Medan Aviation Polytechnic undergo Field Work Practice at PT. Mulya Sejahtera Technology, focusing on aircraft lighting systems. Aims and scope of paper: This paper discusses the evaluation of the Boeing 737-300 lighting system at PT. Mulya Sejahtera Technology Bandung, based on Field Work Practice involving trainees in maintenance, inspection, and troubleshooting across multiple divisions. Methods: Using a descriptive observational approach, trainees engage in one month of daily maintenance, document tasks, and receive supervisor evaluations. Data is gathered through observation, practice, and feedback. Result: Fieldwork Practice provides valuable hands-on experience, which significantly enhances trainees' technical skills, problem-solving abilities, and understanding of the complexity and importance of lighting systems. Trainees successfully apply classroom theory into real-life maintenance scenarios, develop effective communication skills, and adapt to a professional work environment. Conclusion: Evaluation of the Boeing 737-300 lighting system at PT. Mulya Sejahtera Technology Bandung confirms its crucial role in flight safety and comfort. While most components meet standards, some require periodic maintenance and replacement due to aging. Routine inspections are essential to maintain optimal performance and regulatory compliance.
Advances In Sustainable Materials And Green Construction Technologies: A Review Putri Wiji Rahayu Rahayu; Adamu Abubakar Muhammad
International Journal of Sustainable Engineering Innovations Vol. 2 No. 1 (2026): International Journal of Sustainable Engineering Innovations (February 2026)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v2i1.148

Abstract

Background of Study: Climate change, driven by human-induced greenhouse gas emissions, presents a global crisis. The construction sector is a primary contributor, responsible for 30–40% of global energy use and over 30% of emissions throughout the building life cycle. Despite innovations like low-carbon materials and Building Information Modeling (BIM), current research remains fragmented. A significant gap exists in integrating technical, economic, and environmental aspects into a single analytical framework. Aims Paper: This paper aims to identify trends in sustainable materials and green technologies through a systematic review. It evaluates their performance across technical, environmental, and economic dimensions while formulating future research directions to achieve sustainable development goals. Methods: A Systematic Literature Review (SLR) was conducted using the Scopus database (2016–2025). Five core keywords were used to identify relevant studies, which were then cleaned using OpenRefine and visualized via VOSviewer. Elicit AI assisted in screening and synthesizing the final 12 journal articles. Result: Analysis of 12 articles shows that experimental studies (50%) and Multi-Criteria Decision-Making (25%) are the dominant methodologies. Research primarily focuses on optimizing specific materials like waste-based concrete and geopolymers. While material innovation is a priority, there is limited integration of technical data with long-term Life Cycle Assessment (LCA) or life-cycle cost analysis. Cocnlusion: Current sustainable construction research emphasizes technical material optimization through experimental approaches. While decision-support models are evolving, empirical integration of the circular economy and LCA remains limited. Future research must adopt holistic frameworks, expand data sources, and include diverse geographical case studies to support effective sustainability practices.
Sustainable Engineering Innovations for Renewable Energy Systems: A Systematic Literature Review of Technologies, Performance, and Environmental Impacts Deki Saputra; Mohammad Qais Rezvani
International Journal of Sustainable Engineering Innovations Vol. 2 No. 1 (2026): International Journal of Sustainable Engineering Innovations (February 2026)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v2i1.150

Abstract

Background of study: The transition to sustainable energy is essential to mitigate climate change. While renewable sources like solar and wind are key to decarbonization, their adoption is hindered by performance intermittency. Current research is often fragmented by technology type, lacking an integrated framework that simultaneously addresses engineering innovations, technical performance, and environmental sustainability. Aims paper: This study aims to synthesize sustainable engineering innovations by integrating technological development with operational performance and environmental impact assessments. The scope is limited to 20 peer-reviewed articles from the Scopus database published between 2019 and 2025. Methods: The research follows a Systematic Literature Review (SLR) design and PRISMA 2020 guidelines. Data were analyzed using Biblioshiny for descriptive statistics and VOSviewer for thematic and network visualization Result: Findings show an annual scientific growth rate of 44.22%. Key innovations focus on hybrid energy systems, smart grids, and energy storage. Recent trends indicate a shift toward digitalization, IoT-based management, and environmentally optimized materials. Conclusion: Sustainable engineering innovations significantly enhance system efficiency and reliability. Although they reduce greenhouse gas emissions, environmental performance varies by technology. The study concludes that interdisciplinary, system-level approaches are vital for achieving global sustainability goals.
Neuromorphic Computing Chips for Edge AI: A Comprehensive Analysis of Brain-Inspired Hardware Architecture for Real-Time Intelligent Systems Anwar Ali Sathio; Chiragh Kumar Maheshwari
International Journal of Sustainable Engineering Innovations Vol. 2 No. 1 (2026): International Journal of Sustainable Engineering Innovations (February 2026)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v2i1.151

Abstract

Background of study: Edge computing devices like autonomous robots and IoT sensors need sophisticated AI for real-time decisions, but conventional processors consume 15-300 watts during inference, creating critical limitations for battery-powered deployments. GPU-based accelerators face memory bottlenecks and high energy costs from data movement, making sustained autonomous operation impractical. Aims of paper: This research compares neuromorphic platforms (Intel Loihi 2, IBM TrueNorth, BrainChip Akida) against conventional accelerators (NVIDIA Jetson, Google Coral) to evaluate if neuromorphic architectures can solve edge AI energy efficiency challenges across five representative workloads. Methods: Using an experimental design with hardware benchmarking and power analysis, we evaluated five edge AI workloads. ANOVA and regression modeling were then applied to rigorously compare computing paradigms while controlling for variables. Result: Neuromorphic platforms demonstrated 15-50× improved energy efficiency versus conventional GPU accelerators for event-driven workloads. Intel Loihi 2 achieved 2,400 inferences/joule at 1.8 watts versus 180 inferences/joule at 18.5 watts for NVIDIA Jetson. IBM TrueNorth operated at 70 milliwatts for pattern recognition. BrainChip Akida achieved 94.6% accuracy on keyword spotting at 0.8 watts. Event-driven processing exhibited 0.4ms latency versus 5.1ms for frame-based systems. Neuromorphic chips maintained stable performance without active cooling below 65°C, while conventional accelerators required thermal management above 85°C. Conclusion: Neuromorphic processors (0.6-5W) excel in power-efficient edge AI for event-driven data. While hybrid architectures optimize performance, adoption is hindered by immature software ecosystems, limited training frameworks, and a 2-4% accuracy gap compared to conventional methods.
Forest Fire Alert System Using Satellite Imagery, Machine Learning, and GPS-Based Early Warning Mechanism Anwar Ali Sathio; Doulat Ram; Abdul Aziz Khan; Sameer Ali
International Journal of Sustainable Engineering Innovations Vol. 2 No. 1 (2026): International Journal of Sustainable Engineering Innovations (February 2026)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsei.v2i1.152

Abstract

Background of study: Wildfires pose a critical threat to global ecosystems, biodiversity, and human safety, with climate change intensifying fire frequency, scale, and unpredictability. Traditional wildfire detection approaches often suffer from delayed response, limited coverage, and insufficient automation, which restrict effective mitigation and early intervention. Aims and scope of paper: This paper aims to design and evaluate an intelligent Forest Fire Alert System that integrates satellite remote sensing, machine learning models, Internet of Things based environmental sensing, and real time alert communication to enable early wildfire detection and proactive risk assessment. Methods: The proposed system employs a Convolutional Neural Network to detect active fire regions from multispectral satellite imagery, while a Random Forest classifier estimates wildfire risk levels based on meteorological variables and IoT sensor data. Geospatial positioning through GPS supports precise location mapping, and a web-based dashboard disseminates real time alerts to forestry authorities for rapid response. Result: Experimental evaluation demonstrates strong performance of the proposed framework. The CNN model achieved an accuracy of 94.7 percent, precision of 92.3 percent, recall of 96.1 percent, and an F1 score of 94.1 percent. The Random Forest model obtained an accuracy of 88.2 percent with a ROC AUC value of 0.91, indicating reliable fire risk prediction capability. Conclusion: The integrated Forest Fire Alert System outperforms conventional detection methods in terms of accuracy, detection speed, and automation. The proposed approach provides a scalable, IoT enabled, and proactive solution for intelligent wildfire monitoring and management under evolving climatic conditions.

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