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403 articles for “real-time data processing”
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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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Raspberry Pi-based Self-driving Car Technologies: A Review of Hardware and Software Integration
Abstract: An assessment of the state, possibilities, and difficulties of self-driving car technology. Autonomous vehicles (AVs), also referred to as self-driving cars, are automobiles that can navigate and function without the need for human involvement. They make decisions, sense their environment, and traverse routes safely by combining sensors, cameras, radar, lidar, and sophisticated algorithms. The advancement of autonomous vehicles holds the capacity to completely transform the transportation sector by enhancing security, …
Published in International Journal of Electronics Automation · Vol. 2, Issue 2, 2024 · pp. 1–6 Read article
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Multimodal Generative AI for Vehicular Applications at Edge
Abstract: This paper explores how the rapid advancements in vehicular technology, including autonomous driving and intelligent transportation systems, have driven the need for real-time data processing and decision-making. Multimodal generative AI, when deployed at the edge, offers a powerful solution for vehicular applications by leveraging diverse data sources such as video, audio, sensor inputs, and environmental data. This paper explores the integration of multimodal generative AI with edge computing in vehicular …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 27–34 Read article
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Develop a Data Science Approach for Optimizing Energy Consumption
Abstract: Optimizing energy consumption has become a critical challenge in the era of sustainability and increasing energy demand. Efficient energy management is essential to address environmental concerns, reduce costs, and ensure resource availability for future generations. This project leverages data science techniques to evaluate and improve energy consumption across diverse sectors, including residential, industrial, and commercial domains. By integrating advanced analytics, machine learning models, and real-time data processing, the project aims …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 31–44 Read article
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Design, Development, and Optimization of Autonomous Robots for Enhanced Performance
Abstract: Autonomous robots are transforming industries by executing complex tasks with minimal human intervention, improving efficiency, precision, and adaptability across various domains such as manufacturing, healthcare, logistics, and exploration. Their performance relies on a synergy of robust hardware design, intelligent control mechanisms, and advanced optimization techniques. This paper explores the key components of autonomous robots, including sensor integration, locomotion systems, control architectures, and decision-making frameworks that enable autonomous operation in dynamic …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 22–30 Read article
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Critical Review of Impact of UNIX in Development of Military Computing Paradigms
Abstract: The evolution of military computing systems has been profoundly influenced by the integration and continuous advancement of UNIX operating systems since their inception in the early 1970s. This paper presents a comprehensive review of the pivotal role UNIX has played in shaping the foundational architecture of modern military computing—spanning areas such as command-and-control infrastructures, real-time data processing, mission-critical software, and cybersecurity protocols. By tracing the historical development and technical progression …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 08–16 Read article
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Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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How Scientists Look for New Pathogens Before They Spread
Abstract: Emerging infectious illnesses are a persistent danger to global health. They often come from unexpected places, such wildlife reservoirs, changes in the climate, or human activities. Finding new diseases before they create epidemics is one of the biggest problems in modern epidemiology. This article talks about how scientists use genetic monitoring, field sampling, and real-time data processing to find, track, and describe new infectious organisms in a way that works …
Published in International Journal of Pathogens · Vol. 3, Issue 1, 2026 · pp. 11–17 Read article
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Design and Implementation of an IoT-based Traffic and Parking Management System Integrated with GIS for Urban Environments
Abstract: As urbanization accelerates, managing traffic flow and parking availability has become increasingly challenging. This article presents the design and implementation of an internet of things (IoT)-based traffic and parking management system integrated with geographic information systems (GIS) to address these challenges in urban environments. The proposed system utilizes a network of IoT sensors to monitor traffic flow, congestion levels, and parking space availability in real time. The data collected by …
Published in Trends in Transport Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 23–32 Read article
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Real-Time IR Intensity Measurement and Computation for Systems
Abstract: In contemporary defense mechanisms, infrared (IR) sensing has become a fundamental technology for identifying and neutralizing heat-seeking threats, especially concerning aircraft protection. Conventional IR detection systems, such as single-channel radiometers and basic thermal sensors, frequently face restrictions due to low spatial resolution, sluggish data processing, and inadequate user engagement. These constraints can impede the prompt identification of dangers like missile launches or flare activations, potentially endangering mission safety. Additionally, numerous …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 8–13 Read article
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AI-Optimized Itinerary Design: Transforming the Future of Travel Planning
Abstract: The travel industry is struggling to meet the rising demand for efficient and personalized trip planning. Traditional methods often lack real-time updates and fail to adapt to individual preferences, necessitating innovative solutions. This study presents an AI-powered travel planner utilizing the Gemini API to enhance itinerary creation. By analyzing user preferences, interests, and real-time data, the system delivers tailored travel recommendations. Leveraging advanced technologies such as cloud computing, machine learning, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 74–82 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
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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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Plc Hmi base testing machine data loger with usb excel data export
Abstract: The PLC-HMI-based testing machine data logger is designed to acquire, process, and log real-time sensor data using a PLC analog input card. This system is developed for industrial applications requiring accurate measurement, monitoring, and data storage. The setup integrates an HMI (Human-Machine Interface) for visualization and control, while a USB-based Excel data export feature ensures efficient data management. The system incorporates four key transducers: 1. Water Flow Sensor – Measures …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 Read article
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Shell Programming with Sensor Systems and Applications for Human Cognition
Abstract: Shell programming provides a flexible interface to sensor systems, enabling robust scripting for real-time data acquisition and processing, as well as integration with perception components. Such sensors have human analogs—tactile, physiological, and behavioral—and are increasingly embedded within health, mobile, and smart environments to capture fine-grained details of human cognition. Using shell scripts, the system can automatically collect sensor data, fuse multimodal data, and perform adaptive behavioral monitoring, allowing researchers and …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 41–45 Read article
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AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review
Abstract: Pharmacovigilance is very important in drug safety as it monitors, identifies and prevents adverse drug reactions (ADR). Conventional pharmacovigilance systems are usually limited by underreporting and delay in signal detection as well as the inability to scale up. The pharmacovigilance sphere is undergoing a seismic shift with the arrival of AI. The use of AI-driven tools, such as machine learning and natural language processing, is transforming how ADR detection is …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 01–07 Read article
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Jowar Millet Crop Monitoring and Analysis Robot (JMAR): A Smart Solution for Plant and Soil Health in Jowar Millet Farming
Abstract: Farmers cultivating jowar millet (Sorghum) face significant challenges in maintaining crop health and optimizing yield due to the limitations of traditional plant disease detection and soil health assessment methods. Visual inspection and indigenous knowledge are labour-intensive, time-consuming, and often inaccurate, while soil monitoring requires specialized equipment that is not always affordable or accessible. These issues hinder timely intervention and can lead to crop losses and soil degradation. To address these …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Realtime Life Cycle Assessment, Synthesizing Life Cycle Inventory with Business Process Management, Sustainable Growth in the Fourth Industrial Revolution
Abstract: A prevalent methodology for evaluating the ecological impacts of processes and products throughout their entire life cycle is known as Life Cycle Assessment (LCA). This approach involves scrutinizing each phase, encompassing the extraction of raw materials, manufacturing, utilization, and disposal. Nevertheless, conventional LCA methods often fail to account for the dynamic nature of industrial processes and are deficient in real-time data. The Life Cycle Inventory (LCI), a pivotal component of …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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Global Supply Chain Agility Through ERP Systems: A Decision Support Model for Emerging Economies
Abstract: In today’s highly dynamic and interconnected global markets, supply chain agility—the capacity to sense environmental changes and respond rapidly and effectively—has emerged as a critical success factor. This is particularly significant for firms operating in emerging economies, where market volatility, infrastructural limitations, policy uncertainties, and resource constraints pose persistent challenges. Enterprise Resource Planning (ERP) systems, with their ability to integrate cross-functional processes, centralize data, and provide real-time decision-making support, offer …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 31–37 Read article
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Data to Diagnosis: A Systematic Review of AI/ML in Healthcare
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article