Offloading in fog computing for IoT: Review, enabling technologies, and research opportunities

M Aazam, S Zeadally, KA Harras - Future Generation Computer Systems, 2018 - Elsevier
The digital world is expanding rapidly and advances in networking technologies such as 4G
long-term evolution (LTE), wireless broadband (WiBro), low-power wide area networks …

A systematic review of drone based road traffic monitoring system

I Bisio, C Garibotto, H Haleem, F Lavagetto… - Ieee …, 2022 - ieeexplore.ieee.org
Drone deployment has become crucial in a variety of applications, including solutions to
traffic issues in metropolitan areas and highways. On the other hand, data collected via …

Deep PCA based real-time incipient fault detection and diagnosis methodology for electrical drive in high-speed trains

H Chen, B Jiang, N Lu, Z Mao - IEEE Transactions on Vehicular …, 2018 - ieeexplore.ieee.org
Incipient fault detection and diagnosis (FDD) is a key technology for enhancing safety and
reliability of high-speed trains. This paper develops a real-time incipient FDD method named …

Domain adaptation from daytime to nighttime: A situation-sensitive vehicle detection and traffic flow parameter estimation framework

J Li, Z Xu, L Fu, X Zhou, H Yu - Transportation Research Part C: Emerging …, 2021 - Elsevier
Vehicle detection in traffic surveillance images is an important approach to obtain vehicle
data and rich traffic flow parameters. Recently, deep learning based methods have been …

A real-time vision system for nighttime vehicle detection and traffic surveillance

YL Chen, BF Wu, HY Huang… - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
This paper presents an effective traffic surveillance system for detecting and tracking moving
vehicles in nighttime traffic scenes. The proposed method identifies vehicles by detecting …

An efficient optimal neural network-based moving vehicle detection in traffic video surveillance system

A Appathurai, R Sundarasekar, C Raja, EJ Alex… - Circuits, Systems, and …, 2020 - Springer
This paper presents an effective traffic video surveillance system for detecting moving
vehicles in traffic scenes. Moving vehicle identification process on streets is utilized for …

QoI-aware multitask-oriented dynamic participant selection with budget constraints

Z Song, CH Liu, J Wu, J Ma… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
By using increasingly popular smartphones, participatory sensing systems can collect
comprehensive sensory data to retrieve context-aware information for different applications …

Image-based learning to measure traffic density using a deep convolutional neural network

J Chung, K Sohn - IEEE Transactions on Intelligent …, 2017 - ieeexplore.ieee.org
Existing methodologies to count vehicles from a road image have depended upon both
hand-crafted feature engineering and rule-based algorithms. These require many …

[HTML][HTML] 3d-net: Monocular 3d object recognition for traffic monitoring

M Rezaei, M Azarmi, FMP Mir - Expert Systems with Applications, 2023 - Elsevier
Abstract Machine Learning has played a major role in various applications including
Autonomous Vehicles and Intelligent Transportation Systems. Utilizing a deep convolutional …

[PDF][PDF] Automatic traffic density estimation and vehicle classification for traffic surveillance systems using neural networks

C Ozkurt, F Camci - Mathematical and Computational …, 2009 - pdfs.semanticscholar.org
It is important to know the road traffic density real time especially in mega cities for signal
control and effective traffic management. In recent years, video monitoring and surveillance …