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51 articles for “Traffic Predictions”
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Multi-Layered AI-Driven Security in Wireless Ecosystems
Abstract: The proliferation of next-generation wireless technologies, from 5G/6G networks to the pervasive Internet of Things (IoT), has birthed a hyperconnected digital ecosystem of unprecedented scale and dynamism. This interconnectedness, however, introduces a vast and volatile attack surface, rendering conventional, signature-based security paradigms fundamentally obsolete. This paper posits that the only viable defense is an offensive, self-adaptive one, predicated on the integration of artificial intelligence (AI) directly into the wireless security …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article
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Safe Travel: Road Accident Analysis, Severity Prediction, and Safe Route Mapping
Abstract: Road accidents pose a significant threat to public health, resulting in millions of injuries and fatalities annually. With an estimated 1.2 million lives lost and 20 to 50 million people injured each year, the escalating trend of traffic accidents demands urgent attention. To address this issue, specialists utilize advanced algorithms such as random forests to analyze historical road crash data, aiming to predict accident hotspots. By identifying patterns and trends …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 3, 2024 · pp. 39–44 Read article
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Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
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Study Of Uber-Related Data Using Machine Learning
Abstract: This paper describes the operation of the machine learning algorithm used in the Uber database, which contains data generated by the Uber Movement for a few locations in Hyderabad and the big apple City. Uber is known as a peer-to-peer program. This program connects you to the nearest drivers available to take you to your destination. This database includes Uber capture data with information such as time, ride date additional …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 9, Issue 2, 2022 · pp. 1–6 Read article
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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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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article
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In Silico Prediction of Multitarget Mechanism of Quinoline and Its Analogs on Phosphoinositide-3-Kinase Pathway Proteins
Abstract: Objective: Phosphoinositide 3-kinases (PI3Ks), the target of rapamycin (PI3K/Akt/mTOR, PAM), are a family of enzymes that play a role in the growth, proliferation, differentiation, motility, survival, and intracellular trafficking of cells, all of which are essential for healthy cellular function and are also connected to cancer. In this study, quinoline and its derivatives were employed to analyze its inhibition activity on the phosphoinositide-3-kinase pathway. Methods: In this work, eight phytocompounds …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 1, 2023 · pp. 57–76 Read article
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Smart Tracks: Navigating Urban Transit with IoT-enabled Bus Networks
Abstract: Public transportation is a lifeline for countless individuals globally, providing essential connectivity for daily commutes to work and school. However, numerous challenges such as bus delays and inefficient space on the buses often hinder the travel experience. It's crucial to resolve these issues to achieve an efficient public transport system. A promising solution lies in the adoption of an IoT-based application. With this technology, one can track the real-time location …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 1–8 Read article
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Mathematical Modeling Analysis of India's Accident &Use of Fly Ash and Polymers in Road Safety
Abstract: Accident predicting models (APMs) are exceptionally strong tools for adaptation and mitigation strategies because they have the ability to predict both the severity and frequency of crashes. Road accidents are a major problem all throughout the world, especially in developing countries. Understanding the key variables that contribute can assist in reducing the frequency of traffic collisions. This study also discovered recent developments on fly ash, green composites, other polymer materials …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 488–499 Read article
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AI-Driven Intelligent Energy Management System for Enhancing Electric Vehicle Efficiency and Range
Abstract: Electric Vehicles (EVs) are crucial in mitigating the emission of greenhouse gases and facilitating sustainable transportation. Their performance is however limited by the capacity of the battery, unpredictable weather conditions and ineffective use of energy. The paper suggests an AI-based Intelligent Energy Management System (IEMS) to increase EV efficiency and driving range. The suggested system combines machine learning (ML), model predictive control (MPC), and real-time data analytics to optimize power …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 2, 2026 Read article
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Pothole Detection utilising Machine Learning: A Review
Abstract: Potholes must be found and fixed quickly in order to maintain infrastructure, maximize transportation systems, and guarantee road safety. Using the Sequential API and the Keras library, this study presents a neural network model for pothole detection. Convolutional layers with ReLU activation, global average pooling, dense layers with dropout, and softmax activation for binary classification make up the model architecture. Image loading, resizing, array conversion, labeling, shuffling, normalization, and one-hot …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 35–43 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. 1–8 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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A Study on the Use of AI and Sensors in Aerospace
Abstract: The synergistic combination of modern sensors including artificial intelligence (AI) has significantly changed the aeronautics industry's ongoing quest for increased safety, efficiency, and autonomy. The examination of the critical role these technologies play throughout the whole aerospace lifecycle from design and production to flight operations and maintenance is examined in this research. The eyes and ears of contemporary aircraft, sensors give an unparalleled amount and quality of real-time data about …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 25–34 Read article
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Design and Implementation of BLDC Motor Driven Electric Vehicle Using MPPT Controller
Abstract: Minimal and medium power applications benefit greatly from BLDC motor efficiency, high torque-to-inertia ratio, large energy volume, low maintenance requirements and wide speed control range. Resistance found that by deleting phase current sensors and regulating the basic frequency switching of the voltage source inverter (VSI), the proposed control algorithm lowers power losses caused by high frequency switching. With Modern days fuel prices soaring so high for common people, electrical engineers …
Published in Trends in Electrical Engineering · Vol. 12, Issue 1, 2022 · pp. 41–51 Read article
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An approach of Computer Vision Methods for Driver’s Drowsiness and Yawn Detection
Abstract: Numerous studies have demonstrated that 4,444 traffic crashes are primarily caused by driver drowsiness. Due to advancements in digital computer systems, tiredness behaviour may now be studied by researchers worldwide. The goal of this project is to increase road safety by preventing accidents caused by sleepy drivers. To view the driver's face, use real-time facial recognition technology. A driver's attentiveness and reaction time may be impacted by weariness, which raises …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 21–26 Read article
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An Intelligent Modelling system for Automotive Vehicles
Abstract: In this paper it’s about the development of artificial intelligence that has fuelled technological advancements. Self-driving automobiles are an example of an innovative development. Nowadays, you may work or sleep in your car while driving to your destination without touching the steering wheel or accelerator. This project aims to create a workable model of a self-driving car capable of traveling on multiple tracks, including curved, straight, and straight followed by …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 32–40 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Methodology for Evaluating Driver’s Attitudes towards Transportation Demand Management Strategies in Lahore, Pakistan
Abstract: The transportation demand management (TDM) strategies consider as an important tool to solve urban congestion related problems both in objective and subjective manner. This study attempted to explore attitudes of rickshaw, taxi, and truck drivers towards soft and hard strategies considering driver’s various lifestyles and attitudes. Structural equation modeling (SEM) technique used in order to predict driver’s behavior towards each specific TDM strategy using the behavioral theories as a frame …
Published in Recent Trends in Civil Engineering & Technology · Vol. 2, Issue 1-3, 2012 · pp. 78–92 Read article