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85 articles for “driving behavior analysis”
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Fleet Guard: Advanced Fleet Management and Vehicle Monitoring System
Abstract: FleetGuard: Advanced Fleet Management and Vehicle Monitoring is a game changing IoT solution, crafted using Flutter in the Dart language, set to revolutionize conventional fleet management practices. It seamlessly integrates software and hardware components, with a primary focus on Tire Pressure Monitoring Systems (TPMS) and GPS sensors. This innovative system offers real-time tire pressure monitoring, predictive maintenance, and driver behavior analysis, emphasizing efficiency and safety, ultimately reducing operational costs, and …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 2, 2023 · pp. 18–24 Read article
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ESP32-Based Vehicle Security and Driver Safety System
Abstract: This paper presents an ESP32-based intelligent vehicle security and driver safety system designed to improve both automobile protection and road safety through advanced sensor integration and real-time monitoring. The proposed system combines biometric authentication, driver behavior analysis, obstacle detection, and emergency communication into a single compact platform. A fingerprint sensor (R307) is used to provide secure vehicle access, ensuring that only authorized users can start the vehicle. To enhance driver …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 2, 2025 · pp. 9–18 Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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Damping Analysis of Composite Drive Shaft using Computational methods
Abstract: Drive shaft used in automotive is a critical component which comes under the influence of different types of loads in operation. Torsional loading is one of the prime causes contributing to its failure. Most of the research on drive shaft was focused on evaluating natural frequency, torsional strength, buckling torque using analytical approach and also using FEM. This project work deals with the analysis of damping behavior of E-glass/epoxy composite …
Published in Journal of Mechatronics and Automation · Vol. 1, Issue 2, 2014 · pp. 33–38 Read article
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Damping Analysis of Composite Drive Shaft using Computational methods
Abstract: Drive shaft used in automotive is a critical component which comes under the influence of different types of loads in operation. Torsional loading is one of the prime causes contributing to its failure. Most of the research on drive shaft was focused on evaluating natural frequency, torsional strength, buckling torque using analytical approach and also using FEM. This project work deals with the analysis of damping behavior of E-glass/epoxy composite …
Published in Trends in Mechanical Engineering & Technology · Vol. 4, Issue 2, 2014 · pp. 33–38 Read article
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A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
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Time-Series Analysis of Uber Ride Trends
Abstract: This article provides an in-depth analysis of Uber's data analytics, clarifying its crucial role in revolutionizing the transportation industry. It provides vital insights for stakeholders by carefully examining rider patterns, driving behaviors, and market dynamics. This study provides a thorough knowledge of Uber's impact on urban transportation and socio-economic landscapes by combining existing research and proposing fresh approaches. Uber is a digital company that has made multiple attempts to leverage …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 34–38 Read article
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Impact of Fracture in Geometrical, Material, and Load Rate Characteristics on J-Integral
Abstract: The present study investigates the influence of load rate, geometrical parameters, and material properties on the J-integral behavior of AA2050-T84 aluminum-lithium alloy using three-dimensional elastic–plastic fracture mechanics (EPFM) analysis. Finite element simulations were carried out using the ABAQUS software to evaluate crack driving forces in compact tension (C(T)) specimens under various mechanical and thermal conditions. The study focuses on the combined effects of strain rate, temperature-dependent strain hardening, specimen thickness …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 38–45 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Gatividhi Guard: The Activity Guardian—Revolutionizing Security Information and Event Management (SIEM) Technology
Abstract: In the dynamic landscape of cybersecurity, organizations confront increasingly intricate cyber threats that necessitate sophisticated security measures. Conventional systems such as Security Information and Event Management (SIEM) systems face ongoing challenges, they often struggle to effectively detect and mitigate sophisticated attacks within extensive data sets. To address these limitations, the introduction of Gatividhi Guard signifies a paradigm shift in SIEM technology. Gatividhi Guard is an innovative SIEM platform leveraging advanced …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 1, 2024 · pp. 29–44 Read article
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Enhancing Customer Engagement with AI-Driven Movie Recommenders: Integrating Neural Collaborative Filtering, Sentiment Analysis, and Conversational Agents
Abstract: In today’s competitive digital landscape, user engagement is a critical factor for the success of entertainment platforms, especially those offering movie recommendations. This study introduces a comprehensive AI-driven framework designed to enhance customer interaction, satisfaction, and loyalty through the intelligent integration of multiple deep learning models. The system combines three core components: Neural Collaborative Filtering (NCF) for generating personalized movie recommendations based on user behavior and preferences, Long Short-Term Memory …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 45–54 Read article
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KSK Approach: An AI-Driven IoT Based Decision Making System’s Study
Abstract: Internet of Things (IoT) has promised a world of interrelated devices, generating vast amounts of data. Traditionally, IoT systems trusted on preprogrammed procedures and human intervention to process data and make decisions. This approach often struggled to hold the sheer size and density of IoT data, leading to inefficiencies and missed opportunities. However, the true budding of that data lies not simply in its collection, but in its interpretation and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 14–25 Read article
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Sentiment Analysis for Financial Predictions: A Review
Abstract: AbstractSentiment analysis is one of the popular research areas in computer science, as it finds its application in numerous areas like finance, election and product reviews. Behavioral economics suggests that decision of investing in financial markets is driven by feelings like greed, fear etc. With widespread adoption of technology and digitization of corporate disclosures, news and social media platforms, and information expressed through words can be mined and used to …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 59–68 Read article
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Image-Based Quantitative Mapping of Structure Property Relationships in Polymer Composite Materials
Abstract: The performance of polymer composite materials is intrinsically governed by their microstructural architecture, which is shaped by manufacturing conditions and constituent interactions. Despite extensive experimental characterization efforts, establishing transparent and quantitative structure–property relationships from microstructural images remains a challenge. In this study, an explainable image-driven framework is developed to systematically correlate microstructural features with composite property indicators. Microstructure images are processed to identify voids, fibers, and filler phases, from which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 188–196 Read article
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Measuring Social Media’s Impact on Impulse Buying Behavior
Abstract: This study investigates the influence of social media on impulse buying behavior, focusing on how various platforms drive spontaneous purchases and the psychological and demographic factors that contribute to this behavior. Using a mixed-method approach, the research combines quantitative surveys with qualitative insights to offer a comprehensive analysis. We explore how different types of content, such as targeted advertisements, influencer endorsements, and user-generated media, impact consumer impulses. The study examines …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 1, 2025 · pp. 14–22 Read article
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IoT-based Black Box Monitoring for Vehicle Crash Data Analysis and Improving Safety
Abstract: Road accidents are a significant global concern. This project proposes an Internet of Things (IoT)-based black box monitoring system for vehicles to enhance road safety through comprehensive crash data analysis. The system expands on traditional black boxes by incorporating various sensors (accelerometers, gyroscopes, GPS) and potentially in-cabin cameras (with privacy safeguards). This data offers a deeper understanding of crash dynamics, including impact severity, vehicle motion, and safety system deployment timing. …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 3, 2024 · pp. 7–13 Read article
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The Effect of Dynamics and Mass Transfer Limitation on the Kinetic Growth Rate of Methane Gas Hydrates
Abstract: Hydrate management aims to prevent impediments to fluid flow in pipes caused by hydrate deposition. To achieve this goal effectively, a comprehensive understanding of the thermodynamics and kinetics of hydrate formation is essential for predicting their equilibrium conditions, quantifying the amount of deposition, and estimating the associated risk. Hydrate growth studies are a relatively new field, and independent laboratory experiments have shown that hydrate growth is controlled by heat transfer, …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 76–84 Read article
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The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 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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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article