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109 articles for “Monitoring and Maintenance”
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IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction
Abstract: Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 28–37 Read article
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AI-Driven Predictive Maintenance Framework for Intelligent Vehicle Health Monitoring
Abstract: The accelerated development of smart and connected car systems made the necessity to find the accurate and real-time predictive maintenance solutions which would minimize the number of unexpected failures as well as increase the cars on-road safety. The current paper proposes an artificial intelligence-based hybrid predictive maintenance system that combines Long Short-Memory (LSTM) networks and the XGBoost predictor to provide a potent vehicle fault diagnosis, Remaining Useful Life (RUL) prediction, …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–17 Read article
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Visual Recognition with Convolutional Neural Networks for Object Detection
Abstract: Various research and development have taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self-driving cars, face detection by social media apps and law enforcement software’s google lens and so on. The proposed system deals with design and implementation of an efficient way of training a GPU using python libraries to process and …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 07–13 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Smart City Based Manhole Monitoring System
Abstract: Urban environments are increasingly reliant on complex underground infrastructure networks, with manholes serving as critical access points for maintenance, inspection, and drainage. However, traditional manhole monitoring methods, often manual and labour-intensive, can be inefficient and prone to human error. This can lead to serious safety and health hazards, such as accidents caused by open manholes, exposure to harmful gas leaks, and infrastructure damage from overflows due to undetected blockage This …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 1, 2024 · pp. 27–34 Read article
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Advancements in Polymer-Based Sensors and Actuators for Structural Health Monitoring in Aerospace: A Comprehensive Review of Emerging Trends
Abstract: Structural health monitoring (SHM) has emerged as a critical aspect of aerospace engineering, aiming to ensure the safety and reliability of aircraft structures throughout their operational lifespan. In aerospace engineering, structural health monitoring is one of the most important aspects of aerospace engineering. It aims to ensure that aircraft structures are safe and reliable over their entire service life. Polymer-based actuators and sensors have attracted a lot of attention because …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 173–193 Read article
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IoT-Based Public Toilet Monitoring System
Abstract: Public restroom maintenance is critical to urban hygiene and requires good resource management to secure hygiene, sustainability, and costs. This project presents the design and implementation of a real-time monitoring system for public restrooms, including IoT-based sensors, to measure key environmental factors, such as ammonia concentration, ambient light, and water level. The system can continuously monitor ammonia concentrations to detect poor air quality, opening an intervention window to remedy the …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 15–25 Read article
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QR Based Plant Care System
Abstract: The QR Based Plant Care System is an innovative digital solution developed to improve plant monitoring, maintenance, and information management through the integration of QR code technology with smart agricultural practices. Traditional plant care methods mainly depend on manual record keeping, handwritten labels, and human observation, which often result in data loss, inconsistency, and inefficient plant management. With the increasing demand for sustainable agriculture and efficient resource utilization, there is …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 32–40 Read article
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Predictive Maintenance Strategies for Safety-critical Mechanical Systems
Abstract: Ensuring the reliability and safety of industrial systems is essential, especially in high-risk sectors such as aerospace, manufacturing, and energy. Predictive maintenance (PdM) has become a crucial approach for minimizing operational failures and improving maintenance efficiency. This research introduces an advanced PdM framework that enhances industrial safety by integrating Internet of Things (IoT) technology, machine learning (ML), and big data analytics. By enabling real-time monitoring and predictive fault detection, this …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 12–17 Read article
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Pothole Detection utilising Machine Learning: A Review
Abstract: Potholes must be found and fixed quickly in order to maintain infrastructure, maximize transportation systems, and guarantee road safety. Using the Sequential API and the Keras library, this study presents a neural network model for pothole detection. Convolutional layers with ReLU activation, global average pooling, dense layers with dropout, and softmax activation for binary classification make up the model architecture. Image loading, resizing, array conversion, labeling, shuffling, normalization, and one-hot …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 35–43 Read article
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Integrate AI and IoT to Develop Sustainable Polymer Structural Materials Processing Optimization: Enabled Monitoring Strategies for Performance and Lifecycle Assessment
Abstract: The need for long-lasting structural polymer materials that are both environmentally friendly and highly mechanically effective is driving demand for these materials as the industrial sector continues to grow. Optimizing processes, saving energy, detecting faults, and monitoring structures are all hindered by conventional polymer manufacture. This study suggests an AI-IoT system for environmentally friendly production of structural polymer materials to get around these problems. Tools for evaluating system performance and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 169–192 Read article
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A Review on Transforming Patient Pathways: The Impact of Pharmaceutical Software on Drug Manufacturing and Safety Monitoring
Abstract: The development, production, and safety monitoring of pharmaceuticals are being revolutionized by incorporating digital technologies. Throughout drug lifecycles, pharmaceutical software which includes cloud-based systems, automation, data analytics, and artificial intelligence (AI) has emerged behind efficiency and innovation. Real-time monitoring, predictive maintenance, and process optimization are made possible in manufacturing by software tools like Digital Twins, Manufacturing Execution Systems (MES), and Quality Management Systems (QMS). These technologies improve batch consistency, lower …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 40–46 Read article
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A Review on Social Distancing ID Card
Abstract: The frequency of fire accidents in homes, industries, and public spaces has increased due to electrical faults, human negligence, and flammable materials. Traditional fire-fighting systems often depend on human presence and manual intervention, which delays the response time. To overcome this limitation, this project presents an Automatic Fire Extinguisher System based on Arduino and IoT technology for real- time detection and suppression of fire. Gas, temperature, and flame sensors are …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Leafguard: Smart Plant Health Detection
Abstract: Machine learning techniques, including traditional (shallow) ML, deep learning (DL), and augmented learning (AL), are being increasingly utilized for leaf disease classification. These methods involve feature extraction, data augmentation, and transfer learning to enhance model effectiveness and reduce the need for labeled data. The success of machine learning approaches in this domain hinges on the quality and quantity of data available. LeafGuard is a cutting-edge device with intelligent sensing systems …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 32–39 Read article
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Smart Infrastructure Systems: A New Era in Civil Engineering and Infrastructure Management
Abstract: Civil engineering has experienced a significant technological shift due to the adoption of smart infrastructure systems. The integration of the Internet of Things (IoT), artificial intelligence (AI), and big data analytics has facilitated real-time monitoring, predictive maintenance, and improved infrastructure management. These advancements have transformed the planning, design, and operation of roads, bridges, water systems, and buildings. By employing smart sensors and AI-driven algorithms, engineers can now optimize the entire …
Published in Recent Trends in Civil Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 38–43 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Digital and Sustainable Innovations for Zero-Waste Manufacturing
Abstract: The integration of digital technologies and sustainable practices in manufacturing is crucial for addressing global issues like resource depletion, pollution, and waste. Zero-waste manufacturing has emerged as a transformative approach to minimize environmental impact and boost production efficiency. This paper explores how digital and sustainable innovations support this goal. Industry 4.0 technologies— such as IoT, AI, Big Data, and robotics—enable real-time monitoring, predictive maintenance, and optimized resource use. Sensors and …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 3, 2025 · pp. 34–42 Read article
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Petroleum Engineering’s Future in a Changing Energy Environment
Abstract: Concerns about climate change, rapid technological advancement, and the expanding deployment of renewable energy sources are driving a profound transformation in the global energy sector. Within this evolving landscape, petroleum engineering remains a critical discipline, ensuring a reliable and efficient energy supply while adapting to increasingly stringent sustainability expectations. This article examines the future trajectory of petroleum engineering by analyzing how digitalization, advanced reservoir characterization, and enhanced oil recovery techniques …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 61–66 Read article
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Leveraging IoT and AI for Real-Time Monitoring and Optimization of Polymer Production Processes
Abstract: Integrating the Internet of Things (IoT) and Artificial Intelligence (AI) technology provides a transformational potential for the polymer manufacturing business, allowing for real-time monitoring and better control of production processes. This paper explores the synergistic application of IoT and AI to achieve greater efficiency, sustainability, and quality control in polymer manufacturing. IoT sensors and devices may capture massive volumes of data from different phases of the manufacturing process, delivering real-time …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1–16 Read article