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675 articles for “scalable”
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Optimized Text Extraction and E-Repository Development of Hindi and Punjabi Documents Using OCR and NLP Techniques
Abstract: Increase in digitalization of content in the form of text content necessitates powerful document and text extraction systems, particularly for Indian languages such as Hindi and Punjabi. The existing Optical Character Recognition (OCR) solutions support major scripts such as English, leaving a research opportunity for effective recognition of Devanagari and Gurmukhi scripts. This study recommends a modified text extraction algorithm based on Tesseract OCR, accompanied by preprocessing steps of conversion …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 3, 2025 · pp. 35–43 Read article
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Adaptive Machine Learning Framework for Navigation Control of Autonomous Drones
Abstract: The rise of autonomous drones has expanded UAV applications across sectors like surveillance, delivery, agriculture, and rescue operations. However, traditional navigation systems face limitations in adapting to dynamic environments. This study proposes an AI-driven adaptive navigation framework that leverages real-time sensor data, reinforcement learning, and adaptive control strategies to enhance drone autonomy, scalability, and security. The system processes mission inputs, environmental data (from LiDAR, cameras, GPS, and weather sensors), and …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 1–7 Read article
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Routing Protocols in FANETs with Future Enhancements
Abstract: Flying Ad Hoc Networks (FANETs), which are swarms of Unmanned Aerial Vehicles (UAVs), are an emerging solution which revolutionized the area of mission-critical and infrastructure-less communication systems. These networks provide real-time data transfer for use cases such as disaster relief, battlefield observation, environmental monitoring, and 6G-based smart cities. However, the dynamic profile of FANETs, which is defined by high 3D mobility, limited energy resources, unstable wireless links, and constant topology …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 8–13 Read article
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IoT-Based Real-Time Weather Monitoring System
Abstract: In the evolving landscape of the Internet of Things (IoT), real-time environmental monitoring has become increasingly vital across various domains, including agriculture, smart cities, and climate research. This study presents the design and implementation of an IoT-based real-time weather monitoring system that utilizes the ESP32 microcontroller in conjunction with AWS cloud services. Temperature and humidity data are captured using onboard sensors and transmitted using the MQTT protocol to AWS IoT …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 3, 2025 · pp. 19–25 Read article
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Reviewing Threat Detection Methods in SaaS Platforms Through the Use of Adaptive Cloud Security Models
Abstract: Software as a Service (SaaS) solution has revolutionized the contemporary business processes as scalable and service-on-demand solution on cloud networks. Yet, this expansion has brought in sophisticated cybersecurity risks because of a multi-tenant environment facing the internet in the SaaS environment. The key to assure the service availability and protection of the data stored off-site is effective threat detection in such dynamic ecosystems. This review article seeks to discuss the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 Read article
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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An Analysis of Graph Database in Data Modelling and Analysis for a Recommendation System
Abstract: This research work focuses on graph databases, mainly Neo4j databases, in recommendation systems for e-commerce websites. The importance of research is that it explains how graph databases efficiently handle the complex relationship between user-items, which is difficult for traditional databases. Sparsity, limited diversity, and high setup costs are the challenges traditional databases face. This research work overcomes these problems using Ne04j with Cypher query language and graph algorithms (PageRank, Shortest …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 33–39 Read article
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IOT Based Smart System for Parameter Control Interfaced with Android and Cloud
Abstract: The smart embedded system enables real-time monitoring and control of multiple parameters motor speed, LCD brightness, temperature, and humidity through both manual input and remote Android application. The system consists Raspberry Pi 4 Model B as the central processor, integrated with a DHT11 sensor, L298N motor driver, LCD display, and potentiometers. Cloud connectivity is achieved using Firebase to synchronize data between the hardware and a custom-built mobile application. Real-time feedback …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 11–22 Read article
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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A Meta-Analysis of the Role of Serverless Computing Models in Modern e-Healthcare Systems
Abstract: The integration of serverless computing models in e-healthcare systems represents a paradigm shift in healthcare technology infrastructure. This meta-analysis examines the role, benefits, and challenges of serverless architectures in modern healthcare applications, focusing on studies published between 2019 and 2025. Serverless computing offers unprecedented scalability, cost-efficiency, and operational flexibility, making it particularly suited for healthcare applications handling variable workloads such as medical imaging processing, real-time patient monitoring, and electronic health …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 49–58 Read article
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Recent Trends and Techniques in the Advanced Microcontroller Bus Architecture (AMBA) Protocol: A Comprehensive Review
Abstract: ARM has created the Advanced Microcontroller Bus Architecture (AMBA) that is used as the main method for communication on chips in today’s embedded systems. Since AMBA is built to scale and combine with other components, it allows data transfer to high-performance and low-power components easily. The paper discusses how AMBA protocols have evolved and presents new trends of producing higher data rates, conserving energy, and lowering latency. This study offers …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 9–15 Read article
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A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 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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Advancements in Thin Film Coatings for High-Efficiency Electronics and Communication Devices
Abstract: Thin film coatings have become integral to the development of high-efficiency electronics and communication devices, offering enhanced performance, miniaturization, and multifunctionality. This review delves into recent advancements in thin film technologies, focusing on their applications in semiconductors, optoelectronics, and communication systems. We explore various deposition techniques, including atomic layer deposition (ALD), chemical vapor deposition (CVD), and solution-based methods like spin coating, highlighting their impact on device efficiency and scalability. The …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 2, 2025 · pp. 19–24 Read article
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IoT and Smart Sensors for Structural Health Monitoring: Trends, Challenges, and Future Directions
Abstract: Structural Health Monitoring (SHM) plays a critical role in ensuring the safety, resilience, and sustainability of civil infrastructure systems. In recent years, the convergence of Internet of Things (IoT) technologies and smart sensor systems has revolutionized the field of SHM. This integration enables continuous, real- time monitoring, facilitates predictive maintenance, and reduces the costs associated with structural inspections. IoT-based SHM frameworks leverage wireless sensor networks, cloud computing platforms, and intelligent …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 1–6 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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A Review Paper of Automated Driving & ADAS Technologies
Abstract: Automated driving and Advanced Driver Assistance Systems (ADAS) are transforming road mobility, promising enhanced safety, improved traffic efficiency, and greater accessibility. This review presents a comprehensive synthesis of core technologies, system architectures, sensor modalities, perception and decision-making algorithms, and evaluation methodologies underpinning contemporary ADAS and automated driving. We provide a detailed discussion of the functional components—sensors (camera, radar, LiDAR, ultrasonic), localization, perception, prediction, planning, control, and human–machine interfaces—and how these …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–7 Read article
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OBD-II Big Data–Driven ML and AI-Based Virtual Sensing for Fuel Economy, Component Health, and Carbon Intelligence
Abstract: The rapid growth of connected vehicles has led to the large-scale availability of high-frequency On-Board Diagnostics II (OBD-II) data; however, much of this data remains underutilised, as existing studies and commercial systems typically address fuel economy, maintenance, or emissions in isolation or rely on additional physical sensors. Such fragmented and sensor-dependent approaches limit scalability and increase system cost, particularly in high-volume and resource-constrained vehicle markets. To address this gap, this …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 39–50 Read article
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A Trust-Enhanced Security Architecture for Authenticating Customer Records in Banking Institutions
Abstract: The growing digital disruption of banking and financial services has completely altered the face of customer onboarding, money transactions, and financial service deliveries. Even as digital technologies provide unparalleled levels of efficiency and accessibility for consumers of financial services, they have also presented new challenges that are equally daunting. Among the growing number of financial threats that digital technology has spawned is the risk of synthetic identity fraud. Unlike identity …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 16–22 Read article
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Power and Area - Aware Recursive Multiplier Architecture Utilizing Polymer Composites for Neural Network Acceleration
Abstract: Approximate computing is widely applied in error - tolerant systems as an effective technique to enhance circuit performance by deliberately allowing occasional inaccuracies instead of strictly ensuring precise results for every computation. Among the fundamental building blocks of digital systems, multipliers play a crucial role in signal processing, control systems, and machine learning applications; however, they demand significant power, silicon area, and timing resources. Leveraging error - tolerant approximate multipliers …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1320–1337 Read article