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108 articles for “Edge devices”
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Monitoring Health of Edge Devices in Real-Time
Abstract: Monitoring all the edge devices in an enterprise environment or an edge computing environment can be a daunting task due to the sheer volume of edge devices deployed throughout an enterprise. As the size and complexity of computer environments grows, it is becoming more difficult to evaluate and recognize factors which restrict efficiency and scalability. Application developers and system administrators need tools that is easy to use so that they …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 2, 2020 · pp. 17–25 Read article
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Low-Power Reconfigurable Digital Filter Design Using FPGA for IoT Edge Devices
Abstract: The rapid evolution of the Internet of Things (IoT) has led to an exponential increase in the deployment of edge devices that continuously process real-time sensor data under strict power, latency, and computational constraints. Digital filtering remains a critical operation in these devices, supporting tasks such as noise removal, data conditioning, and feature extraction for intelligent decision-making. However, conventional filter implementations on microcontrollers or fixed digital signal processors often struggle …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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Energy-efficient Image Classification on Edge Devices: Implementation and Evaluation
Abstract: Image classification is a computer vision problem where an algorithm determines a class or label for a given image. Various real-time applications like object recognition, medical diagnosis, person recognition, etc. Image classification property on edge devices is useful for autonomous vehicles, surveillance, and healthcare and internet of things deployments. The advancement of deep learning based methods and graphics processing units (GPU) devices allows efficient processing locally. The study utilizes a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 10–18 Read article
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Accurate & Efficient Plant Disease Detection using Transfer Learning with Edge Impulse
Abstract: Transfer learning is a powerful machine learning technique that allows optimization of pre-trained models for related tasks on small datasets. In this research paper, we explore the application of Edge Impulse & transfer learning for plant diseases and aim to detect on edge devices more effectively at low cost. We collected and preprocessed many plant images and used this data to fine-tune a neural network model pre-trained by Edge Impulse. …
Published in Recent Trends in Sensor Research & Technology · Vol. 10, Issue 1, 2023 · pp. 30–41 Read article
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IOT based Smart Traffic Signal Violation Monitoring System using Edge Computing
Abstract: Monitoring the traffic signal surveillance camera by a group of police administrators can be a daunting task due to the sheer volume of data(videos)that must be collected and analyzed. In developing countries such as India, traffic police department need a easy way to catch the vehicle owners who have violated the traffic signal rules. Currently, they are collecting the video near the traffic signal for 24*7 and the administrators are …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 2, 2020 · pp. 10–16 Read article
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MXene-Infused Conductive Nano-Polymers for Edge-Computing Enabled Flexible Environmental Monitoring Devices
Abstract: MXene-infused conductive polymer composites have emerged as highly promising materials for next-generation flexible environmental monitoring devices because they combine electrical conductivity, mechanical flexibility, analyte sensitivity, and compatibility with low-power electronics. In this work, a Ti₃C₂Tₓ MXene–TPU/PVA conductive nano-polymer composite was developed as a multifunctional sensing platform for edge-computing enabled environmental monitoring. The composite was fabricated by dispersing MXene nanosheets into a thermoplastic polyurethane/poly (vinyl alcohol) (TPU/PVA) matrix, coating the conductive …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 298–309 Read article
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Deep Learning models for real time detection of crop diseases in the Maharashtra/Mumbai district
Abstract: This research project addresses the critical agricultural challenge of crop disease management in the Maharashtra region of India by leveraging modern deep learning techniques. The primary objective is to identify, implement, and compare the efficacy of various deep learning architectures—including Convolutional Neural Networks (CNNs), MobileNet, and EfficientNet—for the real-time classification of diseases in key crops such as cotton, soybean, and sugarcane. A custom dataset of agricultural images specific to Maharashtra's …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 36–48 Read article
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How small circuits power big technology in the world of VSIL
Abstract: Very Small Integration Level (VSIL) circuit technology represents an emerging class of ultra- compact, low-power electronic design methodologies that enable the creation of highly efficient and scalable systems. This article explores the fundamental principles behind VSIL circuits, including device miniaturization, optimized layout strategies, adaptive power management, and noise-resilient architectures. We also look into the methodical engineering of VSIL circuits to satisfy the ever-tougher performance, robustness, and long- term energy-efficiency demands …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 44–53 Read article
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Green and Edge-Aware Computing: Rethinking Cloud Infrastructure for Sustainability
Abstract: Cloud computing has transformed the way organizations access and manage information technology resources, providing flexible, scalable, and cost-efficient services that support today’s data-driven world. Despite these advantages, the rapid expansion of large-scale cloud infrastructures has resulted in rising energy consumption, significant heat generation, and a growing environmental footprint. This research focuses on advancing green cloud computing by examining methods that reduce power usage while maintaining high performance. Key strategies include …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 17–24 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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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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Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 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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Next-Gen Techniques for Bottleneck Detection in High-Performance Computing
Abstract: Modern computing systems face new challenges in bottleneck detection and mitigation due to their increasing complexity which stems from multi-core architectures alongside distributed platforms and real-time processing needs. Traditional methods like hardware profiling and static analysis which used to work well now struggle to keep up with the changing conditions of dynamic system behaviors and diverse computing environments along with variable workload patterns. The current limitations restrict their capability to …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 09–14 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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Thermally Adaptive Bio-Inspired VLSI Interconnect Model for Next-Generation Embedded Systems
Abstract: The increasing complexity of next-generation embedded systems has intensified the challenges associated with power dissipation, thermal instability, signal integrity, and interconnect reliability in Very Large- Scale Integration (VLSI) architectures. This research proposes a thermally adaptive bio-inspired VLSI interconnect model designed to enhance communication efficiency and thermal resilience in advanced embedded platforms. The proposed model integrates bio-inspired adaptive routing principles with dynamic thermal-aware interconnect management to optimize data transmission under varying …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 1–11 Read article
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Real-Time Deepfake Detection in Video Conferencing Systems
Abstract: Deepfake technology presents non-exemplary threats to video conferencing platforms, enabling advanced fraud, impression and misinformation campaigns worth billions annually. Current detection methods either exhibit latencies exceeding 100ms or rely on server-side cloud processing, raising privacy concerns. This paper presents DeepConfGuard, a lightweight hybrid architecture combining MobileNetV2 for spatial feature extraction, a bidirectional LSTM with attention for temporal modelling, and EfficientNetV2 for refinement. It reaches 94.8% accuracy with 85 ms end‑to‑end …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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Edge Computing Assisted Polymer Composite Biosensors for real time medical Analytics
Abstract: The fast development of healthcare technologies has generated the increased need of real-time, correct, and effective medical monitoring systems. Polymer composite biosensors have come out as a viable solution since they are flexible, biocompatible and highly sensitive in detecting physiological and biochemical signals. Nevertheless, traditional cloud-based data processing systems bring about latency, bandwidth issues, and privacy risks, and thus are not suitable to use in time-sensitive medical services. In order …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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DESIGN AND FABRICATION OF THERMAL INSULATED OVERHEAD WATER TANKS
Abstract: Overhead water containers are essential for storing water in residential and commercial structures, but because of varying weather, they are sometimes subject to extreme temperature swings. During the summer, the average temperature regularly surpasses 50°C. In residential and commercial structures, above water tanks are essential for water garages; but, due to changing climate conditions, they may be subjected to high temperature changes on a regular basis. The tanks are primarily …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 32–40 Read article
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Fabrication and Study of Multiwall Carbon Nanotube based capacitor electrodes for Energy Storage Applications
Abstract: Current supercapacitors gift numerous wonderful boundaries that critically inhibit the performance,power, and electric capacitance of strength garage devices. Supercapacitors gift an thrilling prospect that has infinite packages in renewable strength garage and cutting-edge day digital devices. In current years thethrilling improvement of carbon nanotubes (CNTs) has offered a bonus in electrode improvement. CNTs, but useful for his or her improved electrode floor place, have extreme boundaries concerning conductivity and electrode …
Published in Journal of Semiconductor Devices and Circuits · Vol. 8, Issue 3, 2021 · pp. 56–60 Read article