A technological proposal for vehicle detection in the context of Smart Cities

2019 ◽  
Author(s):  
Luis Lopez ◽  
Ricardo Gacitua
Keyword(s):  
Smart Cities ◽  
Vehicle Detection

scholarly journals A Robust Vehicle Detection Scheme for Intelligent Traffic Surveillance Systems in Smart Cities

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 139299-139312 ◽  
Author(s):  
Zhiyuan Wang ◽  
Jifeng Huang ◽  
Neal N. Xiong ◽  
Xiaoping Zhou ◽  
Xiao Lin ◽  
...  
Keyword(s):  
Smart Cities ◽  
Vehicle Detection ◽  
Surveillance Systems ◽  
Traffic Surveillance ◽  
Detection Scheme

scholarly journals A Vehicle Detection Model Based on 5G-V2X for Smart City Security Perception

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Teng Liu ◽  
Cheng Xu ◽  
Hongzhe Liu ◽  
Xuewei Li ◽  
Pengfei Wang
Keyword(s):  
Feature Extraction ◽  
Smart City ◽  
Feature Fusion ◽  
Smart Cities ◽  
Vehicle Detection ◽  
Small Scale ◽  
Detection Accuracy ◽  
Data Set ◽  
Prediction Ability ◽  
Detection Speed

Security perception systems based on 5G-V2X have become an indispensable part of smart city construction. However, the detection speed of traditional deep learning models is slow, and the low-latency characteristics of 5G networks cannot be fully utilized. In order to improve the safety perception ability based on 5G-V2X, increase the detection speed in vehicle perception. A vehicle perception model is proposed. First, an adaptive feature extraction method is adopted to enhance the expression of small-scale features and improve the feature extraction ability of small-scale targets. Then, by improving the feature fusion method, the shallow information is fused layer by layer to solve the problem of feature loss. Finally, the attention enhancement method is introduced to increase the center point prediction ability and solve the problem of target occlusion. The experimental results show that the UA-DETRAC data set has a good detection effect. Compared with the vehicle detection capability before the improvement, the detection accuracy and speed have been greatly improved, which effectively improves the security perception capability based on the 5G-V2X system, thereby promoting the construction of smart cities.

scholarly journals IoT with Cloud Centric Vehicle Detection and Counting System for Smart Traffic Surveillance

2019 ◽  
Vol 9 (2) ◽  
pp. 4862-4866
Keyword(s):  
Road Traffic ◽  
Smart Cities ◽  
Vehicle Detection ◽  
Training Dataset ◽  
Detection Accuracy ◽  
Traffic Surveillance ◽  
Efficient Management ◽  
Detection And Counting ◽  
Bounding Boxes ◽  
Smart Traffic

The efficient management of road traffic is one primary facet of many, in smart cities. Traffic overcrowding can be managed successfully, if prior estimation of the number of vehicles that will pass though a crowded junction in a specific time is known. This paper introduces a methodology which targets vehicle extraction on videos covering vehicles. To resolve the problem of current vehicle detection such as the need of detection accuracy and slow speed, an improved YOLOv3 vehicle detection is utilized. The k-means clustering used to group the bounding box around the vehicle in training dataset. The method for calculation of loss with respect to the length and width of the bounding boxes was recovered through the implementation of the batch normalization process. Finally, to improve the feature extraction of the network the high repeated convolution layer are removed. The experiment results are carried out on the BIT-vehicle validation datasets which shows the improvement of mean Average Precision (mAP) could certainly reach 95.6%.

An AHP-Based Evaluating Model to Evaluate Intelligent Vehicle Detection Technologies in Street Parking Scenario

CICTP 2018 ◽  
2018 ◽  
Author(s):  
Xuejin Wan ◽  
Shangfo Huang ◽  
Bowen Du ◽  
Rui Sun ◽  
Jiong Wang ◽  
...  
Keyword(s):  
Vehicle Detection ◽  
Intelligent Vehicle ◽  
Detection Technologies

Feature and Box Propagation for Video Vehicle Detection

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Yanni Yang ◽  
Huansheng Song ◽  
Zhe Dai ◽  
Wentao Zhang ◽  
Yan Chen
Keyword(s):  
Vehicle Detection

Technologies Disability and Inclusion

2018 ◽  
Author(s):  
Tomas Brusell
Keyword(s):  
Social Media ◽  
Augmented Reality ◽  
Information And Communication Technologies ◽  
Future Development ◽  
Smart Cities ◽  
Communication Technologies ◽  
Modern Technology ◽  
The Social ◽  
The Disabled ◽  
Information And Communication

When modern technology permeates every corner of life, there are ignited more and more hopes among the disabled to be compensated for the loss of mobility and participation in normal life, and with Information and Communication Technologies (ICT), Exoskeleton Technologies and truly hands free technologies (HMI), it's possible for the disabled to be included in the social and pedagogic spheres, especially via computers and smartphones with social media apps and digital instruments for Augmented Reality (AR) .In this paper a nouvel HMI technology is presented with relevance for the inclusion of disabled in every day life with specific focus on the future development of "smart cities" and "smart homes".

Sign in / Sign up

Export Citation Format

Share Document