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310 articles for “Automated”
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Blockchain-Enabled Secure Wireless Communication IoT Networks
Abstract: Cloud-native environments with their distributed environments and transient workloads raise the intrinsic problem of traditional intrusion detection and response systems to unprecedented levels. Modern cloud platforms have rapid elasticity, microservice orientation, and dynamic scaling, which usually exceed the range of centralized security services, contributing to the problem of slower threat detection and a poor ability to contain the threat. The proliferation of the Internet of Things (IoT) gadgets across different …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 10–14 Read article
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Emerging Digital Trends in Virology Software: Optimizing Viral Discovery, Surveillance,and Patient Management.
Abstract: Virology and antiviral therapeutics are being reshaped by rapid advances in computational tools, automation platforms, and virus-focused digital health applications. Software systems now span the entire virology value chain, from in silico viral target identification and antigen design, to AI-supported clinical trial management for vaccines and antivirals, to post-marketing pharmacovigilance and patient-facing mobile tools. This review examines current and emerging software trends relevant to virus studies, emphasizing applications in viral …
Published in International Journal of Virus Studies · Vol. 3, Issue 1, 2026 · pp. 29–38 Read article
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A Review on Digital Twin Technology in Robotics
Abstract: Digital Twin (DT) technology has emerged as a transformative concept in robotics and automation, enabling virtual representation of physical systems, real-time monitoring, and performance optimization. This review explores the foundations of Digital Twin, its integration in robotic systems, key enabling technologies, applications, current challenges, and future research directions. The paper concludes by highlighting how Digital Twin transforms design, control, prediction, and human-robot collaboration.Digital Twin technology is transforming the field of …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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Pneumatic Operated Engine
Abstract: The increasing awareness of fossil fuel depletion & environmental pollution has accelerated the need for the development of sustainable & eco-friendly alternatives to traditional internal combustion engines. Pneumatically operated engines have been identified as a potential alternative for small-scale mechanical power generation owing to their advantages of zero exhaust emissions, noise reduction & operational safety. This paper describes the design, development & performance analysis of a pneumatically operated engine, which …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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The Role of AI-Powered Assessment Tools in Improving Educational Feedback in Nigeria
Abstract: Educational systems in Nigeria face a persistent challenge in delivering high-quality, timely, and personalized feedback, due primarily to large class sizes, heavy teacher workloads, and reliance on traditional assessment methods. This study investigates the potential of integrating Artificial Intelligence (AI)-powered assessment tools to overcome these systemic barriers and improve the quality of educational feedback within the Nigerian secondary school context. Employing a quantitative cross-sectional survey design, data was collected from …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 31–41 Read article
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Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article
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Optimizing Smart Grids and Microgrids
Abstract: The widespread deployment of distributed energy resources, the integration of renewable energy sources, and the digitalization of the energy sector have, in a very short time, radically changed old power systems to more intelligent and resilient networks. The change is mainly about smart grids and microgrids that enable real-time monitoring, decentralized control, and improved power quality. The employment of smart meters, advanced communication platforms, and distributed generation elevates the operational …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 1, 2026 · pp. 44–49 Read article
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Adaptive Street Illumination System with Energy Harvesting
Abstract: This paper presents an Adaptive Street Illumination System with Energy Harvesting, developed using an Arduino Uno microcontroller, Light Dependent Resistor (LDR), Infrared (IR) motion sensors, and piezoelectric transducers. The system addresses the significant energy wastage of conventional street lighting by activating LEDs only when motion is detected during nighttime. The LDR detects ambient light to determine day or night conditions, while IR sensors identify the presence of vehicles or pedestrians. …
Published in International Journal of Electronics Automation · Vol. 4, Issue 1, 2026 Read article
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Importance of Thesaurus in Natural Language Processing for Scholarly Data Extraction
Abstract: The exponential growth of scholarly literature needs advanced methods for efficient data extraction and knowledge discovery. Natural Language Processing (NLP) has emerged as a crucial technology in automating the analysis and organization of academic texts. Among various linguistic resources, thesauri serve as important tool for enhancing semantic understanding by providing structured vocabularies, synonyms, and hierarchical relationships between terms. This paper examines the importance of thesauri in enhancing NLP-based scholarly data …
Published in Emerging Trends in Languages · Vol. 3, Issue 1, 2026 · pp. 19–24 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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The Green Cost of Generative Ai: Environmental Sustainability Implications of Large-Scale Ai Systems
Abstract: Generative Artificial Intelligence (GenAI) has advanced rapidly in scale and complexity, enabling powerful capabilities in automated content creation, multimodal reasoning and real-time decision support across sectors. While these systems offer significant technological and economic benefits, their environmental implications are not fully examined. Large-scale GenAI models rely on high-performance computing infrastructure that consumes substantial energy and resources throughout their lifecycle, raising critical sustainability concerns. This paper offers a sustainability-oriented assessment of …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article
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Innovations in Mineral Science and Engineering for Sustainable Resource Development
Abstract: The growing global demand for mineral resources, coupled with increasing environmental and social concerns, has intensified the need for sustainable approaches in mineral science and engineering. Traditional mining and mineral processing practices, while essential for industrial development, are often associated with high energy consumption, resource depletion, and environmental degradation. In response, recent innovations in mineral science and engineering have focused on improving resource efficiency, minimizing environmental impact, and ensuring long-term …
Published in International Journal of Minerals · Vol. 3, Issue 1, 2026 · pp. 31–36 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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An AI-Driven IoT Framework for Autonomous Quality Assurance in Optical Lens Manufacturing
Abstract: The evolution of high-precision optics—ranging from smartphone micro-lenses to high-end astronomical glass—demands unprecedented accuracy in manufacturing. Traditional inspection methods, reliant on manual sampling or static automated optical inspection (AOI), often fail to bridge the gap between high-speed production and the detection of microscopic surface aberrations. This paper introduces an integrated architecture combining the Internet of Things (IoT) and Deep Learning-based decision-making systems to revolutionize lens quality control. By deploying an …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 36–41 Read article
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Fracture Analysis of Functionally Graded Material (FGM) Plates Using Extended Finite Element Method: A Review.
Abstract: Functionally Graded Materials (FGMs), have drawn a lot of interest in various engineering applications due to their superior mechanical properties and ability to withstand extreme conditions. Fracture analysis in FGMs focuses on understanding how cracks initiate and propagate within these complex materials. The stress distribution becomes irregular due to spatial property variations which produces different crack paths than what occurs in homogeneous materials. The examination of FGM plates under fracture …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 9–15 Read article
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Fracture Analysis of Laminated composite plates using Extended Finite Element Method: A Review
Abstract: Laminated composite plates are used in aerospace, automotive, and marine industries. They feature great durability against fatigue, a high strength-to-weight ratio, and mechanical attributes that may be altered. However, they are prone to fracture and delamination under complex loading, requiring accurate fracture analysis for structural integrity. Traditional finite element methods (FEM) need extensive mesh refinement for modelling crack propagation which increases the computational costs. The Extended Finite Element Method (XFEM) …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 16–25 Read article
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Advances in Energy Systems and Solid State Electronics
Abstract: Solid state technology has become a game changer in the field of modern electronics and energy systems providing faster, safer and more energy efficient solutions for several industries. The performance and dependability of electronic systems have been considerably improved by recent advances in solid state materials, semiconductor devices, and energy storage technologies. Progress in solid-state batteries, wide-bandgap semiconductors, and next-generation integrated circuits is transforming applications in electric vehicles, renewable energy …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Radio Frequency Next-Generation Advances
Abstract: Radio frequency (RF) technology is a key enabler for modern wireless communications, driving the evolution of telecommunications, healthcare, aerospace, defence and the Internet of Things (IoT). Faster, more reliable and energy-efficient communication systems have been developed at a rapid pace due to recent discoveries in RF engineering. This article discusses novel advancements in RF technologies including enhanced antenna design, millimeter-wave communication, software defined radio, smart spectrum management, and RF-based sensor …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article