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414 articles for “Real time analysis”
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Smart Crop Recommendation Using IoT Sensor for Precision Agriculture
Abstract: This study addresses precision agriculture, which leverages modern technologies to enhance farming efficiency and sustainability. This study proposes a Smart Crop Recommendation System using IoT sensors to optimize crop selection based on real-time environmental conditions. The system integrates multiple sensors, including a temperature sensor, flame sensor, soil sensor, moisture sensor, and LDR sensor, to monitor crucial parameters such as temperature, soil moisture, light intensity, and fire hazards. An Arduino microcontroller …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 3, 2025 · pp. 29–41 Read article
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Wireless and Wearable Real-time Health Monitoring Systems: A Review of Recent Developments
Abstract: This paper explores the interdependent relationship between mental and physical health, highlighting the impact of stress and anxiety on the body by introducing an innovative Real- Time Health Monitoring System. This system monitors both mental well-being and physical health using advanced physical health sensors and Facial Emotion Recognition (FER) technology. Leveraging high-precision sensors such as Temperature and pulse oximeters, it continuously monitors vital physiological parameters such as Body Temperature and …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Website Usability Using AI
Abstract: This article introduces a comprehensive framework that leverages artificial intelligence (AI), automated tools, and APIs to enhance the evaluation of website usability. The proposed framework integrates AI-driven models with traditional usability assessment techniques to create a more dynamic and effective evaluation process. Specifically, it utilizes Google Lighthouse to conduct in-depth audits on website performance, search engine optimization (SEO), and accessibility. Additionally, chatbot APIs are incorporated to gather real-time user feedback, …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 · pp. 19–27 Read article
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Solar Tracking System and Battery Management
Abstract: This project focuses on optimizing renewable energy systems by combining a dual-axis solar tracking mechanism with a smart Battery Management System (BMS) to improve solar energy harvesting and storage. The system uses an Arduino Uno microcontroller and Light Dependent Resistors (LDRs) to track the sun's position, enabling the solar panel to adjust its orientation in real-time for optimal sunlight exposure throughout the day. At the same time, the integrated IoT-based …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 2, 2026 Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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3D Printing for Polymer Science Visualization
Abstract: The burgeoning field of 3D printing offers exciting possibilities for various scientific disciplines. This paper explores the potential integration of 3D printing technology within the realm of polymer analysis. While the core focus of memory forensics investigations lies in digital forensics, the concept of 3D printing complex data structures presents intriguing possibilities for the visualization and communication of findings in polymer science. Here, we propose a future research avenue where …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 96–101 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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SmartMed: An AI Powered Platform for Instant Medicine Access and Prescription Understanding
Abstract: Access to medicines during emergencies and the lack of prescription clarity remain significant challenges in modern healthcare systems. Most existing online pharmacy platforms primarily focus on home delivery services and do not provide real-time visibility of nearby pharmacy stock or intelligent prescription interpretation support. This limitation often delays treatment and creates confusion for patients. This paper presents a Smart Medicine Availability, Delivery, and AI Consultation System that integrates real-time pharmacy …
Published in Research and Reviews: A Journal of Medicine · Vol. 16, Issue 2, 2026 · pp. 1–15 Read article
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Optimized Hardware Realization of AES for High-Throughput FPGA Platforms
Abstract: The Advanced Encryption Standard (AES) is the predominant symmetric-key cryptographic algorithm used for securing digital communication across embedded systems, IoT devices, cloud infrastructures, and defense networks. Although software-based AES implementations offer flexibility, they often fail to meet the high-speed, low-latency, and energy-efficient requirements of modern real-time applications. Reconfigurable hardware platforms such as Field-Programmable Gate Arrays (FPGAs) provide a powerful alternative by enabling architectural customization, intrinsic parallelism, and optimized hardware acceleration. …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 11–22 Read article
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Optimizing Urban Mobility with AI-Based Traffic Management
Abstract: Urban mobility is a pressing concern in modern cities, plagued by issues like traffic congestion and pollution. This research involves, "Optimising Urban Mobility with AI-based Traffic Management", delves into the potential of Artificial Intelligence (AI) to revolutionize traffic management. Focusing on AI algorithms, data analytics, and sensor technologies, the research aims to enhance traffic flow, reduce congestion, and improve overall efficiency. Through statistical analysis and simulations, the research evaluates the …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 34–43 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Recent Advancements and Comprehensive Review on Hyphenated Techniques
Abstract: Hyphenated techniques represent a powerful class of analytical methods that combine two or more established techniques – typically a separation method with a spectroscopic detection technique – to achieve enhanced analytical performance. First introduced by Hirschfeld in 1980, the term “hyphenation” refers to the online coupling of such methods, enabling more precise, sensitive, and comprehensive analysis of complex samples. These techniques exploit the strengths of individual methods while overcoming their …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 3, 2025 · pp. 37–50 Read article
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An Empirical Analysis of Bluetooth Low Energy Reliability Challenges for Offline Messaging Applications
Abstract: In today's hyper-connected world, modern communication relies heavily on centralised internet infrastructure, making robust offline messaging solutions increasingly essential. A crucial vulnerability is revealed by network failures, natural disasters, and distant region deployments: communication breaks down when internet connectivity does. Due to its low power consumption and almost ubiquitous availability in contemporary smartphones, Bluetooth Low Energy (BLE) has become a promising candidate for offline, device-to-device communications. This study presents an …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 Read article
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Advances in Non-Invasive NIR-Techniques for Gout Detection and Measurement
Abstract: Recent advancements in non-invasive near-infrared (NIR) spectroscopy techniques have significantly improved the detection and measurement of gout, a common form of inflammatory arthritis. Traditional diagnostic methods for gout, such as joint aspiration and crystal analysis, are invasive and can be uncomfortable for patients. In contrast, NIR spectroscopy offers a promising alternative by enabling real-time, non-invasive assessment of uric acid levels and related biomarkers associated with gout. The integration of portable …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 1, 2025 · pp. 1–8 Read article
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Design of an Integrated Health Monitoring System on an IoT-Based Framework
Abstract: With the advent of industrialization, health ailments have become a major cause of concern owing to an inactive and fast lifestyle, polluted environments, and detrimental eating habits. However, IoT has become a boon for the health sector and humanity on account of its countless benefits, rendering improved quality of service and patient-centric care. An Integrated Health Monitoring System (IHMS) is presented in this paper. This new IoT-based framework integrates wearable …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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Survey Paper on Multilingual Live Call Translation Using Deep Learning
Abstract: This research work surveys cutting-edge language translation technologies, including multi-lingual, real-time translation, voice recognition, speech-to-text conversion, and transcription in the hearing process. The study explores the complex mechanisms behind voice call language translation, focusing on sophisticated machine learning models integrated with cloud-based or local applications to facilitate seamless communication across language barriers. Furthermore, conducting research in live communication analyzes the complexity of text and voice techniques to deliver translated content …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 13–21 Read article
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POLYMER AND COMPOSITE-BASED GEOSYNTHETIC REINFORCEMENTS FOR SEISMIC STABILITY OF SOIL RETAINING STRUCTURES: MATERIALS, MECHANICS, AND PERFORMANCE REVIEW
Abstract: Geosynthetic materials based on polymer and composites have become important items for the structural performance and seismic resilience of the reinforced soil retaining systems. Mechanically stabilized earth walls in recent geotechnical engineering practice are increasingly based on enhanced polymeric reinforcements for enhanced tensile strength, durability, flexibility, and energy dissipation under dynamic loading. High-density polyethylene, polypropylene, polyester, and fiber-reinforced polymer composites are usually used. The present review focus on the recent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 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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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