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675 articles for “scalable”
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
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From Theory to Practice: The Mathematical Foundations of Secure Blockchain Transactions
Abstract: The rise of blockchain technology has transformed the method of conducting secure and decentralized transactions across multiple industries. At its core, blockchain relies on a robust mathematical foundation to ensure data integrity, transparency, and immutability. This paper delves into the theoretical underpinnings that make secure blockchain transactions possible, including cryptographic algorithms, distributed consensus protocols, and mathematical proofs of security. We begin by exploring the role of cryptography, particularly public-key encryption, …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 1, 2025 · pp. 13–20 Read article
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Hydroenergen: A Piezoelectric-Based Raindrop Energy Harvesting System for Sustainable Power Generation and Monitoring
Abstract: The Raindrop Energy Conversion System represents a groundbreaking approach to renewable energy generation by harnessing the kinetic energy of raindrops and water flow from outlets of dams and reservoirs. By utilising innovative piezoelectric transducer plates, the system efficiently converts the impact energy of raindrops into electrical power. Robust insulation and sealing techniques ensure the durability and reliability of the transducer plates, making the system suitable for operation in diverse environmental …
Published in Trends in Electrical Engineering · Vol. 15, Issue 1, 2025 · pp. 35–43 Read article
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Advancing IoT Security through Blockchain-based Approaches
Abstract: The emergence of blockchain technology has revolutionized various industries, including the Internet of Things (IoT), by providing a decentralized and secure platform for data management and transaction processing. However, securing IoT devices and networks remains a significant challenge due to inherent vulnerabilities and the increasing sophistication of cyberattacks. Blockchain-based security approaches have shown promise in addressing these challenges, yet their adoption is hindered by a lack of comprehensive taxonomy and …
Published in Trends in Electrical Engineering · Vol. 15, Issue 1, 2025 · pp. 1–34 Read article
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Key Generation Algorithms Using Difference Equations with Multi-Precision Arithmetic: A Review
Abstract: Modern cryptographic systems rely on robust key generation to secure data and communication. This review explores the integration of difference equations and multi-precision arithmetic for cryptographic key generation, addressing limitations in traditional methods like pseudorandom number generators and chaotic systems. Difference equations produce deterministic yet chaotic sequences ideal for cryptography due to their sensitivity to initial conditions and nonlinearity. However, finite precision arithmetic can lead to periodicity and loss of …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 23–36 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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Advanced Materials for Solar Photovoltaic Cells: Recent Developments and Future Prospects
Abstract: Solar energy is becoming a key component of renewable energy systems due to the global shift to sustainable energy sources. Recent developments in solar photovoltaic (PV) cell materials have resulted in notable gains in scalability, cost-effectiveness, and efficiency. With an emphasis on inorganic, organic, hybrid, and developing materials, this review looks at the most recent advancements in materials for photovoltaic technology. Notably, organic photovoltaics’ offer benefits in flexibility and inexpensive …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article
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Attendance System Based on Facial Recognition
Abstract: Attendance management is a fundamental aspect of educational institutions and workplaces, ensuring accountability, discipline, and operational efficiency. Traditional methods, such as manual roll calls, RFID cards, and fingerprint scanners, are often time-consuming, error-prone, and susceptible to fraud. This research presents an automated attendance management system utilizing face recognition technology to address these challenges effectively. The proposed system employs OpenCV for real-time image processing, the face recognition library for accurate facial …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 28–34 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 Read article
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Advanced Collaboration and Project Management Platform
Abstract: The growing dependence of employees on remote and hybrid working modes worldwide has driven a demand for modern collaborative platforms to optimize project management. All organizations are keen on solutions that enhance workflow efficiency, facilitate seamless communications, and boost overall productivity. The study presents an advancement in project management collaboration and aims at finding solutions to meet those demands, using API integration. The study explores the extent to which API …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 · pp. 11–18 Read article
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Real-Time Video Surveillance Using ESP-32 CAM for IoT Applications
Abstract: The rapid advancements in technology and the growing concerns for security have driven the need for innovative, cost-effective, and scalable surveillance systems. This project presents the development of a smart surveillance system using the ESP-32 CAM module, a compact and low-cost microcontroller integrated with Wi-Fi, Bluetooth, and a high-resolution OV2640 camera. The system is designed to provide real-time monitoring, motion detection, and automated alert features, catering to the security needs …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 26–35 Read article
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A Study of Cloud-Enabled Deep Learning for Monitoring and Predicting Soil Health in Agriculture
Abstract: Soil health is a critical factor in ensuring sustainable agricultural practices and food security. Traditional methods for soil health assessment are often time-consuming, localized, and lack scalability. This study explores the integration of cloud-enabled deep learning techniques to monitor and predict soil health efficiently. Leveraging data from IoT sensors, satellite imagery, and lab-based analyses, a cloud-based framework is proposed to process and analyze soil health parameters such as pH, moisture …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
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RFID-Enabled Smart Shelves and Cart System
Abstract: With the fast-paced development of Radio Frequency Identification (RFID) technology, the retail sector is seeing a revolutionary change to improve stock management, cut operational costs, and improve consumer satisfaction. The comparative advantages of RFID-smart shelves and carts over conventional stock management practices, such as barcode scanning and manual stock management, are investigated in this work. Compared to the other methods, in terms of accuracy, efficiency, cost-effectiveness, and scalability, RFID smart …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 2, 2025 · pp. 31–37 Read article
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Animal Detection in Farms Using Opencv
Abstract: Agriculture plays a fundamental role in sustaining the Indian economy, providing employment and livelihood to a large portion of the population. Despite advancements in farming techniques, one of the persistent challenges faced by farmers is the intrusion of wild animals into agricultural fields. Such intrusions often lead to large-scale crop damage, financial loss, and emotional distress for farmers. Traditional animal deterrent methods, such as manual patrolling, fences, or scarecrows, have …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 Read article
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Bio-Inspired Nanostructured Catalysts for CO2 Valorization: Green Chemistry Approaches in Polymer Nanocomposites for Sustainable Energy Solutions
Abstract: Artificial photosynthesis is a pioneering technology inspired by natural photosynthetic processes, offering a sustainable solution to address global energy crises and mitigate environmental impact. By harnessing solar energy, artificial photosynthesis aims to convert carbon dioxide (CO₂) and water into high-energy chemicals, such as methanol and hydrogen, while concurrently reducing harmful greenhouse gas emissions. This innovative process represents a transformative shift toward carbon-neutral or even carbon-negative energy production, helping reduce dependency …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 38–46 Read article
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Dynamic Modeling and Simulation of Multi-Body Mechanical Systems: A Comprehensive Review of Methods, Tools, and Applications
Abstract: The dynamic modeling and simulation of multi-body mechanical systems (MBS) form a cornerstone in modern mechanical engineering, enabling in-depth analysis of the kinematic and kinetic behaviors of interconnected rigid and flexible components. MBS are foundational to a range of critical applications, from automotive suspensions and aerospace mechanisms to robotics and biomechanical structures. As system complexity and performance requirements increase, accurate and scalable modeling techniques are essential for both design validation …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 35–42 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article