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342 articles for “real-time prediction”
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Artificial Intelligence and Personalized Learning
Abstract: Artificial Intelligence is transforming education by delivering customized learning pathways that align with each learner’s unique abilities and areas for improvement. Traditional teaching often struggles to meet individual needs; however, AI-powered systems analyse learning patterns in real time, ensuring customized lessons. Virtual tutors and AI chatbots provide instant feedback and 24/7 support, improving comprehension. Gamified learning, combined with augmented and virtual reality, transforms education into a more engaging and enjoyable …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 11–18 Read article
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An Overview Mechatronics Systems Design of Modelica-Based Model Predictive Control Strategies for CO₂ Heat Pump Systems
Abstract: The growing adoption of renewable energy technologies poses challenges to energy supply stability, necessitating increased flexibility in energy demand. This paper introduces a Modelica-based Model Predictive Control (MPC) strategy aimed at keeping the supply water temperature within the range of 55°C to 75°C while minimizing energy consumption and electricity expenses throughout a year. A comprehensive, high-fidelity model representing a school building in Oslo, Norway, was developed using Modelica and exported …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 15–27 Read article
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
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Smart Framework for Personal Fuel Expense Tracking and Carbon Emission Assessment
Abstract: This study presents a smart system that is intended to assist individuals and administrators in tracking their fuel costs and keeping an eye on their daily carbon emissions. It makes it simpler to make decisions by examining fuel consumption and its effects on the environment. The technology gathers real-time emissions data from vehicles equipped with Internet of Things devices. It can predict future trends of emissions by utilizing AI-based predictive …
Published in Journal of Thermal Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 36–44 Read article
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Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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Computational Intelligent Techniques for Enhancing the Capabilities and Efficiency of Smart Water Meters
Abstract: In recent years, the realm of smart water meters has undergone a transformative evolution driven by the integration of computational intelligent techniques. This research work embarks on an exploration of the multifaceted applications of these techniques, delving into their profound impact on enhancing the functionality and efficiency of smart water meters. The convergence of artificial intelligence (AI) and machine learning (ML) algorithms with smart water meters presents a paradigm-shifting opportunity …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 66–74 Read article
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Layered Metal–Polymer Hybrid Laminates with Embedded Impact Sensors for Connected Automotive Panels
Abstract: The increasing demand for lightweight, intelligent, and structurally reliable automotive components has accelerated the development of multifunctional hybrid materials capable of simultaneously providing superior mechanical performance and real-time structural health monitoring. In this study, a novel layered metal-polymer hybrid laminate incorporating an embedded flexible impact sensor was developed for connected automotive panel applications. The laminate was fabricated using AA6061-T6 aluminum alloy face sheets and a thermoplastic polyurethane interlayer through hot-press …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Advanced Airline Operations Control System Using NodeJS
Abstract: This research paper presents the development of an Advanced Airline Operations Control System (AAOCS) using NodeJS, a lightweight and scalable JavaScript runtime environment. Leveraging NodeJS's event-driven architecture and non-blocking I/O model, the system facilitates efficient management of flight operations, crew scheduling, resource allocation, and real-time decision-making in the aviation industry. Key features include real-time decision support tools, a microservices-based architecture for scalability, integration with external data sources and APIs, and …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 1, 2024 · pp. 45–51 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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Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Smart Water Harvester
Abstract: Smart water harvester is a wiser use of Data Science in the optimization of rainwater harvesting, taking into account the forecast of precipitation and ideal catchment areas, and basically image processing using machine learning. In that respect, the system, via predictive algorithms like Random Forests, predicts the amount of rainfall by taking into consideration historical and real-time data, while Digital Elevation Models (DEM) and visualization methodologies of images make geographical …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Material-Integrated Energy Management: Role of Advanced Polymers and Composites in Smart Homes
Abstract: The article discusses the possibility of improving the performance as well as the sustainability of smart-home-based energy management systems (EMS) by applying advanced polymeric and composite materials. Smart homes today are placing greater requirements on lightweight, thermally stable, high durability, and electrically conducting compounds in such important aspects of the devices as batteries, substrate layers in solar panels, thermally resistant enclosures, and high efficiency thermal insulation on intelligent appliances. Such …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1361–1374 Read article
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Review On BIM-Based (Revit+Robot Software) Comparative Wind Load Analysis of High-Rise RCC Buildings in Zone-III, IV and V
Abstract: Wind load is one of the most critical factors influencing the design and serviceability of high-rise reinforced concrete (RCC) buildings. As building height increases, wind-induced effects such as storey drift, lateral displacement, and structural stiffness become dominant design considerations. Numerous studies have been conducted using conventional and advanced techniques such as Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and Building Information Modelling (BIM). However, limited research focuses on comparative …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 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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Kisan Mantra: Enhancing Farmer Productivity, A Web-Based Approach for Efficient Crop Harvesting and Problem Diagnosis
Abstract: India's agricultural sector faces persistent challenges, including limited access to expert guidance, difficulties in managing diverse datasets, unreliable weather forecasting, and a lack of real-time monitoring for farm activities and crop quality. Additionally, farm lenders struggle to obtain accurate insights into farm productivity and risks, hindering their ability to provide tailored financial solutions. The sector also grapples with underemployment among educated professionals, limiting their contributions to agricultural advancement. To tackle …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 71–87 Read article
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Use of Artificial Intelligence to Access and Ensure Safe Drinking Water Supply: A Review
Abstract: Ensuring access to safe drinking water is a critical public health challenge. Traditional water quality assessment methods are often labor-intensive and time-consuming. Artificial intelligence offers a promising alternative, providing rapid, accurate, and scalable solutions for monitoring and predicting water quality. This systematic review examines the application of AI. The review highlights various AI models, including artificial neural networks, support vector machines, decision trees, and ensemble methods, in predicting water quality …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 21–28 Read article
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A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Digital Twin-Driven Optimization of Dynamic Covalent Polymer Networks under Real-Time IoT Monitoring
Abstract: The dynamic covalent polymer networks (DCPNs) has the highest allurement because of the reversibility of all of the chemicals and repetitive. The process of convalescence is delayed, the sense of source betrayal and acting relations is too strong. This transport to our material situation is an ever-refrigerated digital twin in this painting which was developed through repetition produced by constant synchronism sensors of the IoT that is constantly refined by …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 137–157 Read article