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546 articles for “machining technologies”
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Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities
Abstract: Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 01–06 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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Enhancing Road Safety: A System for Vehicular Accident Detection, Prevention, and Rescue Alerts
Abstract: The Vehicular Accident Detection, Prevention, and Rescue Alert System is a comprehensive solution aimed at bolstering road safety by integrating multiple advanced technologies. It merges drowsiness detection, alcohol level monitoring, and instant emergency alerts to mitigate accidents and expedite rescue efforts. Modern computer vision and machine learning techniques are used by the Drowsiness Detection Alarm to track driver conduct and spot drowsiness indicators. Upon detecting drowsiness, an immediate alarm is …
Published in International Journal of Solid State Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 7–11 Read article
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IoT-based Heart Attack Prediction System Using Machine Learning
Abstract: Heart disease, particularly heart attacks, is one of the leading causes of mortality worldwide. Timely detection and prompt intervention play a vital role in significantly improving the survival rates of individuals at risk of cardiac events. Unfortunately, most traditional healthcare systems are not equipped with mechanisms for continuous, real-time monitoring of patients' cardiovascular health. This limitation makes it extremely difficult for healthcare providers to identify warning signs early enough to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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Air Flow Analysis in Sensor-Based Aircraft Wings Design
Abstract: Airflow analysis, at its core, is an application of fluid mechanics principles to the specific study of air movement. Airflow analysis plays a crucial role in diverse fields, impacting everything from the comfort of our homes to the efficiency of jet engines. The pursuit of more efficient, safer, and more responsive aircraft wings is a constant driver of innovation in the aerospace industry. The quest for more efficient, safer, and …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 29–39 Read article
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Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Recent Advances and Future Prospects in Digital Twin Technology for Battery Management Systems of Electric Vehicles
Abstract: Digital twin technology in battery management systems (BMS) for electric cars (EVs) represents a major development in the automotive industry. Digital twins provide predictive maintenance, modelling, and real-time monitoring by creating virtual copies of real-time monitoring, actual battery systems. This paper describes the functional components, architecture, and design of Digital Twin technology along with how it may be included into BMS. Emphasizing how consistent data flow from sensors improves battery …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 Read article
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Contribution Of Indian Historical Technology To Development The AI
Abstract: The Indus Valley Civilization (3300–1300 BCE) was among the first in the world to develop advanced metallurgy. They created bronze tools, copper vessels, and intricate metal ornaments. A testament to ancient Indian metallurgy, this rust-resistant iron pillar, built during the Gupta Empire, still stands without significant corrosion, demonstrating an advanced understanding of material science. The study examines key texts and technologies, including Panini’s Ashtadhyayi (a formal system of grammar resembling …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 3, 2025 Read article
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Genomic Selection for Grain Yield in Wheat Using Machine Learning on DArT Molecular Markers: A Comparative Evaluation Across Multi-Environment Trials
Abstract: Genomic selection (GS) predicts complex quantitative traits directly from genome-wide molecular markers, bypassing the need for extensive phenotypic trials and accelerating plant breeding cycles. We conducted a comparative evaluation of seven regression approaches — ridge regression (the machine-learning equivalent of RR-BLUP), Lasso, Elastic Net, Partial Least Squares, linear Support Vector Regression, Random Forest, and Gradient Boosting — for predicting grain yield from 1,279 Diversity Array Technology (DArT) molecular markers genotyped …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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The Molecular Structure of Chemical Compounds by using Quantitative Calculations in Chemistry
Abstract: Computational chemistry has its roots in the early attempts of theoretical physicists, beginning in 1928, to solve the Schrödinger equation using mechanical calculating machines. These calculations verified that the solutions of the Schrödinger equation quantitatively reproduced experimentally observed properties of simple systems such as the helium atom and the hydrogen molecule. These approximate solutions of larger systems and exact solutions of simple model problems allowed chemists and physicists to provide …
Published in Journal of Catalyst & Catalysis · Vol. 12, Issue 2, 2025 · pp. 01–08 Read article
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Alternating Inertia-Based Virtual Synchronous Machine Control for Improved Frequency Regulation of Energy Storage Systems
Abstract: The rapid integration of renewable energy sources (RESs), particularly solar photovoltaic and wind energy systems, has significantly increased the penetration of power electronic converter-based distributed generators (DGs) in modern power systems. While these technologies provide substantial environmental, economic, and sustainability benefits, their widespread deployment has introduced new operational challenges. One of the major concerns is the reduction of system inertia and damping due to the replacement of conventional synchronous generators …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 2, 2026 Read article
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A Novel Approach to Fingerprint Authentication Using Histogram Oriented Gradients for Feature Extraction and Machine Learning Convolution Neural Network for Classification
Abstract: With applied biometrics, it is possible to identify a person by examining a feature vector of attributes derived from their physical and behaviour characteristics. In biometrics, fingerprints have become one of the most famous and well known techniques of identification and authentication. In light of technological advancements and safety, fingerprint recognition has been successfully used in a variety of Civil, Defence, and Commercial applications for more than a decade. The …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 1–12 Read article
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Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration
Abstract: The “Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration” project is a cutting-edge solution for intelligent traffic monitoring, with YOLO v8 (You Only Look Once) serving as the fundamental technology for real-time vehicle detection and traffic counting on roads. In addition to these features, the system interfaces effortlessly with data pipelines and machine learning projects by storing gathered traffic data in CSV (Comma-Separated Values) format. The major goal of …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 20–24 Read article
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The Evolution of Computer Languages: Fundamentals, Paradigms, and Consequences
Abstract: In today’s society, computers are important tools because they let us quickly analyze, store, and share information. A variety of programming languages that let people talk to machines are at the heart of how computers work. These languages, which are divided into low-level and high-level kinds, connect human logic and machine actions. Low-level languages such as machine code and assembly allow direct interaction with computer hardware. In contrast, high-level languages …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 16–28 Read article
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Refrigeration System Performance and Energy Optimization in Food Preservation and Cold Chain Logistics
Abstract: A vital part of the food preservation sector, refrigeration guarantees the durability, security, and quality of perishable food items in the supply chain. The food cold chain, which encompasses the refrigeration systems used during storage, transportation, and distribution, is integral to maintaining food safety and minimizing waste. However, as the global demand for food increases and sustainability concerns rise, energy consumption in refrigeration systems presents a major challenge. Efficient refrigeration …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 22–29 Read article
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Enhancing Security of UPI Payments Through Artificial Intelligence
Abstract: The integration of Artificial Intelligence (AI) into modern digital payment systems has brought about a significant transformation in the banking and financial sector. Among these systems, the Unified Payments Interface (UPI), developed by the National Payments Corporation of India (NPCI), has emerged as one of the most successful real-time payment mechanisms due to its simplicity, accessibility, and efficiency. With the incorporation of AI technologies, UPI has witnessed notable improvements in …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 7–12 Read article
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Sentiment Analysis of E-Commerce Reviews using Machine Learning
Abstract: In e-commerce, sentiment pertains to the emotional responses, opinions, or perceptions that customers have about their online shopping experiences, including factors like product quality, service, and various processes such as ordering, shipping, and customer support. Sentiment analysis, which involves machine learning techniques, plays a crucial role in deciphering these sentiments. By using sentiment analysis, companies can obtain valuable insights from customer feedback from diverse online sources, including social media, surveys, …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 25–37 Read article