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AR and Computer Vision Revolutionize Bridge Inspections

Researchers have developed a bridge inspection method using computer vision and augmented reality (AR) to enhance fatigue crack detection. This innovative approach utilizes AR headset videos and computer vision algorithms to detect cracks, displaying results as holograms for improved visualization and decision-making.

17 Jun 2024

AI and Digital Twins: Revolutionizing System Capabilities

A review in Data & Knowledge Engineering investigates how AI enhances digital twins, highlighting improved functionalities and key research gaps. The integration of these technologies shows promise across various sectors, from healthcare to smart cities.

6 Jun 2024

Carbon-Neutral Mobility Hub Planning Using AI

Researchers introduced a novel AI-based, three-tier scheme for identifying and assessing carbon-neutral mobility hubs, focusing on optimal site selection, suitability analysis, and traffic impact evaluation. The study demonstrated significant reductions in vehicle travel and substantial cost savings, promoting sustainable urban transportation planning.

5 Jun 2024

AI Enhances Pedestrian Monitoring in Train Stations

Researchers employed AI and computational vision techniques to improve pedestrian monitoring in crowded train stations. Utilizing YOLOv7 for object detection and AlphaPose for activity recognition, the study successfully tracked passenger movements and activities, providing critical insights for enhancing station safety and efficiency.

31 May 2024

Advanced Model Boosts Vessel Trajectory Classification

Researchers introduced biSAMNet, a cutting-edge model integrating word embedding and deep neural networks, for classifying vessel trajectories. Tested in the Taiwan Strait, it significantly outperformed other models, enhancing maritime safety and traffic management.

29 May 2024

Blockchain and Drones: A Decentralized Revolution

Integrating blockchain with the Internet of Drones (IoD) promises enhanced security, connectivity, and efficiency in drone applications like delivery, surveillance, and rescue operations.

27 May 2024

Enhancing UAV Safety with Machine Learning

A study in Heliyon introduced a machine learning-based approach for predicting defects in BLDC motors used in UAVs. Researchers compared KNN, SVM, and Bayesian network models, with SVM demonstrating superior accuracy in fault classification, highlighting its potential for improving UAV operational safety and predictive maintenance.

23 May 2024

AI Unveils Key Turbulence Structures

Researchers used eXplainable AI (XAI) to identify critical coherent structures in wall-bounded turbulence, improving predictions of flow states. This novel approach, applicable to complex and high Reynolds number flows, enhances understanding and control of turbulent phenomena in engineering and natural systems.

21 May 2024

Crack the Code: Advanced Method Enhances Train Rivet Inspection

This study proposes an innovative method for detecting cracks in train rivets using fluorescent magnetic particle detection (FMPFD) and instance segmentation, achieving high accuracy and recall. By enhancing the YOLOv5 algorithm and developing a single coil non-contact magnetization device, the researchers achieved significant improvements in crack detection.

17 May 2024

Socioeconomic Dynamics in Ridesourcing Markets

Researchers delve into the complex interplay between socioeconomic inequality, platform profit, and societal welfare in ridesourcing markets through an agent-based simulation model. Their study reveals how disparities drive market dynamics, impacting both travelers and drivers, and highlights the need for nuanced consideration of these factors in shaping the future of ridesourcing economies.

7 Apr 2024

Solar-Powered Hybrid EV Charging Station Design

Researchers present a 4-kW hybrid EV charging station integrating solar power and battery energy storage, offering sustainable, uninterrupted charging while reducing reliance on fossil fuels. Through simulations and performance evaluations, the system demonstrates efficient grid interaction, scalability, and potential for broader adoption, promoting a greener future for transportation.

3 Apr 2024

Enhanced Land Cover Classification in Remote Sensing

Chinese researchers introduce a groundbreaking deep inverse convolutional neural network approach tailored for land cover remote sensing images. This novel method effectively addresses data imbalance, significantly improving classification accuracy and precision, with potential applications in urban planning, agriculture, and environmental monitoring.

2 Apr 2024

NSO-VFC in Internet of Vehicles: Securing the Road Ahead

This article delves into the innovative approach of Network Security Offloading in Vehicle-to-Fog-to-Cloud (NSO-VFC), proposed by researchers from Islamic Azad University, Iran, to address the crucial challenge of securing data offloading in the Internet of Vehicles (IoV) within a fog-cloud federation. By leveraging fog computing and incorporating features such as nonce-based authentication and session key generation, NSO-VFC promises to enhance security, communication performance, and cost-efficiency in IoV environments, paving the way for safer roads, efficient traffic management, and improved environmental monitoring.

14 Mar 2024

Deep Learning and Bayesian Regularization for Urban Planning

Researchers from South Korea and China present a pioneering approach in Scientific Reports, showcasing how deep learning techniques, coupled with Bayesian regularization and graphical analysis, revolutionize urban planning and smart city development. By integrating advanced computational methods, their study offers insights into traffic prediction, urban infrastructure optimization, data privacy, and safety and security, paving the way for more efficient, sustainable, and livable urban environments.

8 Mar 2024

Novel Algorithm for Accurate Weather Monitoring and Enhancing Highway Safety

Researchers presented an innovative algorithm combining frequency and spatial domain techniques to monitor severe weather conditions on highways effectively. Utilizing image processing methods, the algorithm accurately identified rainy days and assessed rainfall intensity, demonstrating its potential to enhance road traffic safety by distinguishing between weather conditions. While successful in daytime monitoring, limitations exist for nighttime data, highlighting areas for future research to address and improve the model's capabilities.

4 Mar 2024

Hierarchical Reinforcement Learning Enhances Multi-UAV Air Combat

Chinese researchers propose a novel approach combining hierarchical reinforcement learning with experience decomposition to boost decision-making efficiency for multiple unmanned aerial vehicles (UAVs) in air combat. Tested and validated using simulation platforms, their method outperforms baseline algorithms, showcasing superior win rates, convergence speed, and stability, promising advancements in UAV-based combat decision-making technologies.

1 Mar 2024

AI-Driven Framework for Real-Time Crash Risk Forecasting at Intersections

Researchers present a cutting-edge framework for real-time crash risk estimation and prediction at signalized intersections, leveraging artificial intelligence and traffic conflict data. By integrating a non-stationary generalized extreme value model and a recurrent neural network, the framework offers proactive insights for safety management and countermeasure implementation, demonstrating high accuracy and potential for real-world applications.

29 Feb 2024

Hierarchical Federated Learning for Smart City AIoT Systems

Researchers introduce a hierarchical federated learning framework tailored for large-scale AIoT systems in smart cities. By integrating cloud, edge, and fog computing layers and leveraging the MQTT protocol, the framework addresses data privacy and communication latency challenges, demonstrating enhanced scalability and efficiency. Experimental validation in Docker environments confirms the framework's feasibility and performance improvements, laying the foundation for future optimizations.

29 Feb 2024

Optimizing Content Caching in Vehicular Networks: A Gale–Shapley Approach

Researchers proposed a novel content caching scheme for fog nodes in 5G-enabled vehicular networks, utilizing a modified Gale–Shapley algorithm to optimize content placement based on the preferences of content providers and vehicles. Their approach effectively reduced content downloading time, improved quality of service, and ensured fair and efficient content placement by considering factors such as content popularity, vehicle connectivity, and channel quality.

21 Feb 2024

Optimizing Electric Vehicle Power: A Novel Energy Management Strategy

Researchers present an innovative energy management strategy (EMS) for electric vehicles (EVs), combining slap swarm optimization and differential flatness control to enhance performance and reliability. The proposed EMS efficiently coordinates power flow among battery, supercapacitor, and motor components, stabilizing voltage, reducing harmonics, and meeting power demand, promising improved EV efficiency and driving range while reducing greenhouse gas emissions.

18 Feb 2024