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62 articles for “Rapid Deployment”
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IoT Security: Issues, Best Practices, and Open Challenges
Abstract: The internet of things (IoT) provides the facility to connect different devices and communicate and share information over the internet. IoT has emerged as a transformative and pervasive technological paradigm, revolutionizing how we interact with our environment and infusing intelligence into everyday objects and devices. This interconnected ecosystem has unleashed a wave of innovative applications across diverse domains, including healthcare, transportation, agriculture, industrial automation, and smart cities. However, as the …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 7–13 Read article
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Experimental Analysis of Axially Compressed Precast Concrete Pressure Pipes Filled with Concrete
Abstract: Humanity has always been at the mercy of natural disasters, which frequently result in widespread devastation and displacement. However, scientific advancements, technological innovations, and extensive research have significantly mitigated the loss of life, property, and essential resources. One of the critical challenges in the aftermath of disasters is providing adequate and timely shelter, food, and medicine to the affected populations, often under constrained resources and logistical difficulties. In response to …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 28–37 Read article
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Reinforcement Learning for Adaptive Sensing with Shape Memory Polymer-Based IoT Nodes
Abstract: The rapid expansion of intelligent sensing in the Internet of Things (IoT) has revealed the pressing need for materials and algorithms capable of self-adaptation in volatile environments. Conventional polymer-based sensors and static control strategies often fail to capture nonlinear thermo-mechanical dynamics, leaving them unsuitable for unpredictable operating conditions. Although prior studies have improved polymer composites or introduced algorithmic optimization independently, few attempts have coupled the adaptability of smart materials with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 370–391 Read article
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Recent Innovations and Trends in Renewable Energy for Offshore Structures
Abstract: The global transition to renewable energy is gaining significant momentum, driven by rapid technological advancements and the urgent need to mitigate climate change. Offshore renewable energy, in particular, is emerging as a critical component in achieving energy security and sustainability. This review provides a comprehensive analysis of recent trends and advancements in offshore renewable energy technologies, including offshore wind, solar, hydrogen, biofuels, and wave energy. Offshore wind energy has witnessed …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 2, 2025 · pp. 1–9 Read article
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Real-Time IR Intensity Measurement and Computation for Systems
Abstract: In contemporary defense mechanisms, infrared (IR) sensing has become a fundamental technology for identifying and neutralizing heat-seeking threats, especially concerning aircraft protection. Conventional IR detection systems, such as single-channel radiometers and basic thermal sensors, frequently face restrictions due to low spatial resolution, sluggish data processing, and inadequate user engagement. These constraints can impede the prompt identification of dangers like missile launches or flare activations, potentially endangering mission safety. Additionally, numerous …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 8–13 Read article
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A Lean Manufacturing Approach for Optimization of Lithium-Ion Battery Supply Chains Management
Abstract: The rise of electric vehicles (EVs), energized by the rapid uptake from customers, is propelling an explosion in demand for -running efficient and economical lithium-ion battery supply chains. In answering the call, this paper delves into the application of lean manufacturing principles to optimize lithium-ion battery (LIB) supply chain management by significantly decreasing waste, lead times, and enhancing overall production efficiency. Lean tools are applied for the analysis of battery …
Published in Journal of Production Research & Management · Vol. 14, Issue 3, 2024 · pp. 9–18 Read article
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Digital Psychiatry: A Narrative Review on AI Positive Role in Mental Health
Abstract: Artificial Intelligence has rapidly evolved into a formidable instrument within the domain of mental healthcare, fundamentally altering the way we understand awareness, diagnosis, intervention and emotional regulation. This narrative review explores AI’s potential to foster positive mental health through tools such as natural language processing, machine learning, deep learning and computer vision. These technologies promise earlier detection of mental disorders, customized treatment plans and responsive emotional support. Yet, alongside these …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 1–13 Read article
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Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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The Future of Mathematics Education in the Era of Artificial Intelligence
Abstract: The rapid integration of Artificial Intelligence (AI) into education is fundamentally reshaping the landscape of mathematics teaching and learning. This study examines how AI-powered tools are converting conventional math training into inclusive, individualized, and data-driven learning environments. Through an in-depth examination of global case studies—including Squirrel AI, Carnegie Learning’s MATHia, Khan Academy, Microsoft Math Solver, DIKSHA, Photomath, ALEKS, and BYJU’S—the study highlights AI’s ability to tailor content, deliver real-time feedback, …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 2, 2025 · pp. 37–44 Read article
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Real-Time Ocean Monitoring and Early Warning Systems with IoT Technology
Abstract: The increasing frequency of extreme weather events, rising sea levels, and threats to marine biodiversity This paper explores the application of IoT in enhancing real-time ocean monitoring and early warning systems, focusing on the deployment of smart sensors, connected buoys, and data analytics to collect key parameters such as temperature, salinity, pH, and wave activity. To preserve and responsibly utilise the seas, oceans, and marine resources in support of sustainable …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 13–24 Read article
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AquaSential: Autonomous UAV-Based Water Quality Monitoring System
Abstract: The increasing occurrence of waterborne health risks and the presence of harmful microorganisms in freshwater environments highlight the need for rapid and continuous water quality monitoring. Traditional laboratory-based testing methods often require significant time and manual sampling, limiting their ability to provide immediate information about changing environmental conditions. This work presents AquaSential, a low-cost, portable, and UAV-ready water quality monitoring system designed for real-time assessment of freshwater bodies. The proposed …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Leveraging Full Stack Data Science for Healthcare Transformation: An Exploration of the Microsoft Intelligent Data Platform
Abstract: The rapid progress of the Fourth Industrial Revolution has been largely driven by the evolution of artificial intelligence (AI), with notable contributions from technologies such as Generative Pre-trained Transformers (GPT). This revolution has seen the convergence of physical, digital, and biological technologies, leading to transformative impacts across various sectors. Data science, serving as a crucial enabler, has enabled the development of intelligent value chains. However, the application of data science …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 1–8 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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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Graphene Based Electronic Skin for Wearable Health Monitoring and Human– review on Machine Interaction, Materials, Structures and AI Integration
Abstract: Graphene-based electronic skin (e-skin) has emerged as a transformative technology for next-generation wearable health monitoring and advanced human–machine interaction (HMI). Owing to its outstanding electrical conductivity, mechanical flexibility, atomic-scale thickness, and biocompatibility, graphene enables the fabrication of ultrathin, conformal, and multifunctional sensors capable of mimicking the sensory functions of natural human skin. Over the past decade, research in this domain has progressed rapidly across four interconnected fronts: material synthesis and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Design, Mathematical Modeling, and Dynamic Optimization of a Speed Breaker-Based Vehicular Kinetic Energy Harvester
Abstract: Decentralized energy harvesting methods are becoming more popular due to rapid urbanization and the rising need for sustainable infrastructure. The road-embedded vehicle kinetic energy harvester (VKEH) design, mathematical modelling, and experimental validation are presented in this work. This paper presents the structural engineering, continuum mathematical modeling, and experimental validation of an optimized road-embedded vehicular kinetic energy harvester (VKEH). The mechanism utilizes a spring- loaded, low-friction rack-and-pinion transmission coupled with a …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 2, 2026 Read article
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A Study on Drone Hacking: Vulnerabilities and Mitigation Techniques
Abstract: This paper explores the current cybersecurity landscape surrounding Unmanned Aerial Systems (UAS), commonly known as drones. With rapid growth in commercial and recreational drone use, the risk of cyber-attacks has also increased. This study highlights real-world vulnerabilities such as GPS spoofing, Wi-Fi hijacking, and firmware exploitation. It also suggests practical mitigation techniques, including encryption, real-time anomaly detection using machine learning, and secure communication protocols. The goal is to support researchers, …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 1–8 Read article
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Technical Advances in Drone Applications for Environmental Surveillance
Abstract: Unmanned Aerial Vehicles (UAVs), or drones, have rapidly evolved into essential tools for environmental monitoring and conservation due to their advanced sensor integration, real-time data acquisition, and autonomous operational capabilities. This review explores the multidisciplinary convergence of drone technologies with environmental science, emphasizing the technical and engineering aspects that drive these applications. The study outlines key UAV system components—including multispectral and hyperspectral imaging, LiDAR, thermal sensing, and real-time GPS-AI integration—highlighting …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 14–20 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article