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289 articles for “Monitoring techniques”
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High-Performance Thin Film Coatings for Corrosion Resistance in Extreme Environments
Abstract: Corrosion is a serious concern in industries such as aerospace, marine, and oil & gas, where materials are exposed to harsh environments. High-performance thin-film coatings have emerged as a critical solution to mitigate this issue, providing a protective barrier against harsh chemical and physical conditions. This review article highlights recent advancements in thin-film coatings designed to enhance corrosion resistance in such environments. The focus is on various coating materials, including …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 11, Issue 2, 2024 · pp. 20–25 Read article
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IoT Integration in Sustainable Agriculture
Abstract: The increasing demand for food production, environmental concerns, and resource limitations have necessitated the adoption of Internet of Things (IoT)-based innovative farming solutions. The current paper introduces an IoT-based system that integrates hydroponics, aquaponics, and poultry to promote sustainability, resource utilization, and agricultural productivity. Conventional farming practices are riddled with ineffective use of resources, uncertain environmental effects, and expensive operations. The new system facilitates real-time monitoring, automated decision support, and …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 69–84 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
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An Overview on Harnessing Microwave Frequencies for Next-Generation Satellite Communication and Earth Observation
Abstract: In the vacuum of space, where traditional cables cannot reach, humanity has woven an invisible, high-speed infrastructure made of oscillating electromagnetic waves. At the heart of this architecture lies the microwave spectrum—the unsung hero that enables everything from global GPS navigation to real-time climate monitoring. The evolution of global connectivity and environmental monitoring is intrinsically linked to the mastery of the microwave spectrum. As satellite constellations transition from traditional Geostationary …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 1–6 Read article
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Fire Monitoring and Suppression System for a Car using by Automation and Existing Technology
Abstract: Fire Monitoring and Suppression System for a car using Automation and Existing Technology presents a comprehensive review of fire monitoring and suppression systems for vehicles. The Project aims to explore the causes of vehicle fires, existing technologies for fire detection and suppression, and a proposed working model for implementing fire safety measures in automobiles. The literature review within the project provides a thorough analysis of the primary causes of fires …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 1, 2024 · pp. 1–10 Read article
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Spatial Distribution and Species Diversity of Marine Bibalves Along the Rocky Intertidal Zone of Veraval, Gujarat, India.
Abstract: The rocky intertidal shoreline of Veraval, located along the Saurashtra coast of Gujarat, serves as a vital habitat for various marine organisms due to its unique composition of rocky- sandy patches and tidal pools. This study was undertaken to evaluate the diversity and spatial distribution of marine bivalves at the Jaaleshwar coast (20º 54’ 36.210’’ N, 70º 21’ 09.090’’ E). Field observations were carried out over nine months from July …
Published in International Journal of Marine Life · Vol. 3, Issue 1, 2026 · pp. 25–30 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Integrated Spatial and Statistical Assessment of Groundwater Quality in Rupbas Tehsil of Bharatpur, Rajasthan: A WQI-based Approach
Abstract: This study presents a comprehensive evaluation of groundwater quality in Rupbas Tehsil of Bharatpur District, Rajasthan, through the application of the Water Quality Index (WQI) and hydrogeochemical techniques. A total of 32 groundwater samples, 16 collected during the pre-monsoon and 16 during the post-monsoon seasons, were analyzed for key physicochemical parameters including pH, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), oxidation-reduction potential (ORP), total hardness (TH), total …
Published in Journal of Water Pollution & Purification Research · Vol. 12, Issue 3, 2025 · pp. 84–93 Read article
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Deep Learning models for real time detection of crop diseases in the Maharashtra/Mumbai district
Abstract: This research project addresses the critical agricultural challenge of crop disease management in the Maharashtra region of India by leveraging modern deep learning techniques. The primary objective is to identify, implement, and compare the efficacy of various deep learning architectures—including Convolutional Neural Networks (CNNs), MobileNet, and EfficientNet—for the real-time classification of diseases in key crops such as cotton, soybean, and sugarcane. A custom dataset of agricultural images specific to Maharashtra's …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 36–48 Read article
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The Potential of Li-Fi for High-Speed Underwater Data Transfer
Abstract: Recently, there has been a growing interest in using underwater communication (UC) to monitor obstacles and marine life in oceans. Unlike conventional methods which struggle due to the absorption of radio waves in water, Li-Fi technology has emerged as a promising solution. Li-Fi utilizes light to transmit data, making it effective for underwater communication as light can penetrate deep into the ocean. In a recent study, researchers successfully demonstrated real-time …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 10–17 Read article
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Hybrid Material Systems for Flexible Electronics Electro-Mechanical Performance and Future Prospects
Abstract: Flexible electronics are transforming the landscape of modern electronic systems, enabling devices that are lightweight, stretchable, and adaptable to complex surfaces. These technologies are particularly impactful in applications such as wearable health monitors, soft robotics, energy harvesting systems, and implantable biomedical devices. At the heart of this evolution are hybrid material systems—engineered composites that combine organic polymers and inorganic nanomaterials to achieve synergistic electro-mechanical properties. These materials address the limitations …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 7–12 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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An Efficient LoRa-Enabled Fault Detection Using Self-Powered IoT Device
Abstract: This study describes a revolutionary internet of things (IoT) solution for effective defect detection in a variety of applications. By utilizing an IoT device that generates energy from the surroundings, the suggested solution gets around the drawbacks of conventional battery-operated gadgets. The suggested approach makes use of a self-sustaining IoT gadget that can capture energy from the surroundings to get beyond the drawbacks of conventional battery-powered IoT devices. Longer functioning …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–13 Read article
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Data-Driven Digital Twin Model for Real-Time Strength Estimation in Polymeric Materials
Abstract: The real-time prediction of mechanical properties in polymeric materials is essential for ensuring quality, consistency, and operational efficiency in modern manufacturing systems. As industrial processes become increasingly complex, traditional trial-and-error approaches to material characterization are no longer sufficient to meet the demands of high-throughput production environments. This study introduces a digital twin-integrated machine learning approach for the real-time estimation of tensile strength in polymeric materials by combining simulation-driven insights with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 246–257 Read article
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Enhancing Wildlife Tourism Management Using Deep Learning and Particle Swarm Optimization (PSO) for Animal Detection in Wildlife Sanctuaries
Abstract: Wildlife tourism is one of the most thriving sectors, faced with huge challenges in terms of safeguarding protected areas. As demand for wildlife experiences accelerates, it becomes necessary to find efficient measures that are friendly to conservation. The use of these advanced techniques in this field such as YOLO and PSO algorithm presents a new dimension on managing wildlife tourism. To harness the abilities of these techniques, this research centers …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 41–50 Read article
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AI-Driven Psychological Profiling on Social Media: Mechanisms, Ethical Breaches, and Regulatory Challenges in Data Inference
Abstract: This literature review examines AI-driven psychological profiling on social media, analyzing 21 academic studies that focus on machine learning techniques such as supervised learning, deep neural networks, sentiment analysis, and natural language processing. These methodologies infer mental health indicators—such as depression, anxiety, and stress—from users' digital footprints, encompassing linguistic patterns, engagement metrics, and temporal behaviors. While these tools offer potential for early detection of psychological distress, they also raise significant …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 1–7 Read article
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Sensor and IoT centered Smart Agriculture by NodeMCU
Abstract: A style of farming that makes use of technology and data to maximize the throughput and efficiency of farming techniques is stated to as smart agriculture. This method of farming is also often referred to as precision farming or digital farming. The fact that this invention in the agricultural sector has the impending to radically transmute how users cultivate and produce food makes it an extremely hopeful and exciting development. …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 3, 2024 · pp. 24–32 Read article
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article