scholarly journals Road Dynamic Object Mapping System Based on Edge-Fog-Cloud Computing

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2825
Author(s):  
Sooyeon Shin ◽  
Jungseok Kim ◽  
Changjoo Moon
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Real Time ◽  
Grid Cell ◽  
Safe Driving ◽  
The Road ◽  
Dynamic Mapping ◽  
Mapping System ◽  
Roadside Unit ◽  
On The Road

Dynamic objects appearing on the road without notice can cause serious accidents. However, the detection ranges of roadside unit and CCTV that collect current road information are very limited. Moreover, there are a lack of systems for managing the collected information. In this study, a dynamic mapping system was implemented using a connected car that collected road environments data continuously. Additionally, edge-fog-cloud computing was applied to efficiently process large amounts of road data. For accurate dynamic mapping, the following steps are proposed: first, the classification and 3D position of road objects are estimated through a stereo camera and GPS data processing, and the coordinates of objects are mapped to a preset grid cell. Second, object information is transmitted in real time to a constructed big data processing platform. Subsequently, the collected information is compared with the grid information of an existing map, and the map is updated. As a result, an accurate dynamic map is created and maintained. In addition, this study verifies that maps can be shared in real time with IoT devices in various network environments, and this can support a safe driving milieu.

CASA: An Alternative Smartphone-Based ADAS

2021 ◽  
pp. 1-41
Author(s):  
Manolo Dulva Hina ◽  
Hongyu Guan ◽  
Assia Soukane ◽  
Amar Ramdane-Cherif
Keyword(s):  
Low Cost ◽  
Electronic System ◽  
Time Data ◽  
Case Scenario ◽  
Safe Driving ◽  
The Road ◽  
Driving Assistance ◽  
Alternative Means ◽  
On The Road ◽  
Driving Assistance System

Advanced driving assistance system (ADAS) is an electronic system that helps the driver navigate roads safely. A typical ADAS, however, is suited to specific brands of vehicle and, due to proprietary restrictions, has non-extendable features. Project CASA is an alternative, low-cost generic ADAS. It is an app deployable on smartphone or tablet. The real-time data needed by the app to make sense of its environment are stored in the vehicle or on the cloud, and are accessible as web services. They are used to determine the current driving context, and, if needed, decide actions to prevent an accident or keep road navigation safe. Project CASA is an undertaking of a consortium of industrial and academic partners. A use case scenario is tested in the laboratory (virtual) and on the road (actual) to validate the appropriateness of CASA. It is a contribution to safe driving. CASA’s contribution also lies in its approach in the semantic modeling of the context of the environment, the vehicle and the driver, and on the modeling of rules for fusion of data and fission process yielding an action to be implemented. In addition, CASA proposes a secured means of transmitting data using light, via light fidelity (LiFi), itself an alternative means of wireless vehicle–smartphone communication.

scholarly journals Integration of Transport-relevant Data within Image Record of the Surveillance System

2016 ◽  
Vol 28 (5) ◽  
pp. 517-527
Author(s):  
Adam Stančić ◽  
Ivan Grgurević ◽  
Zvonko Kavran
Keyword(s):  
Mathematical Model ◽  
Data Processing ◽  
Discrete Cosine Transform ◽  
Programming Language ◽  
Surveillance System ◽  
Basic Assumption ◽  
Review Paper ◽  
Relevant Information ◽  
The Road ◽  
On The Road

Integration of the collected information on the road within the image recorded by the surveillance system forms a unified source of transport-relevant data about the supervised situation. The basic assumption is that the procedure of integration changes the image to the extent that is invisible to the human eye, and the integrated data keep identical content. This assumption has been proven by studying the statistical properties of the image and integrated data using mathematical model modelled in the programming language Python using the combinations of the functions of additional libraries (OpenCV, NumPy, SciPy and Matplotlib). The model has been used to compare the input methods of meta-data and methods of steganographic integration by correcting the coefficients of Discrete Cosine Transform JPEG compressed image. For the procedures of steganographic data processing the steganographic algorithm F5 was used. The review paper analyses the advantages and drawbacks of the integration methods and present the examples of situations in traffic in which the formed unified sources of transport-relevant information could be used.

Trends and Technologies in Big Data Processing

2020 ◽  
pp. 17-42
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Computing Technology ◽  
Time Data ◽  
Big Data Processing ◽  
Real Time Data ◽  
Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

scholarly journals Fog Computing Framework for Smart City Design

2020 ◽  
Vol 14 (01) ◽  
pp. 109
Author(s):  
Mais Haj Qasem ◽  
Alaa Abu-Srhan ◽  
Hutaf Natoureah ◽  
Esra Alzaghoul
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Real Time ◽  
Smart City ◽  
Network Architecture ◽  
Data Exchange ◽  
Fog Computing ◽  
Computing Paradigm ◽  
Network Usage ◽  
The Cost

Fog-computing is a new network architecture and computing paradigm that uses user or near-users devices (network edge) to carry out some processing tasks. Accordingly, it extends the cloud computing with more flexibility the one found in the ubiquitous networks. A smart city based on the concept of fog-computing with flexible hierarchy is proposed in this paper. The aim of the proposed design is to overcome the limitations of the previous approaches, which depends on using various network architectures, such as cloud-computing, autonomic network architecture and ubiquitous network architecture. Accordingly, the proposed approach achieves a reduction of the latency of data processing and transmission with enabled real-time applications, distribute the processing tasks over edge devices in order to reduce the cost of data processing and allow collaborative data exchange among the applications of the smart city. The design is made up of five major layers, which can be increased or merged according to the amount of data processing and transmission in each application. The involved layers are connection layer, real-time processing layer, neighborhood linking layer, main-processing layer, data server layer. A case study of a novel smart public car parking, traveling and direction advisor is implemented using IFogSim and the results showed that reduce the delay of real-time application significantly, reduce the cost and network usage compared to the cloud-computing paradigm. Moreover, the proposed approach, although, it increases the scalability and reliability of the users’ access, it does not sacrifice much time, nor cost and network usage compared to fixed fog-computing design.

scholarly journals Towards a Real-Time Driver Workload Estimator: An On-the-Road Study

2016 ◽  
pp. 1151-1164
Author(s):  
Peter van Leeuwen ◽  
Renske Landman ◽  
Lejo Buning ◽  
Tobias Heffelaar ◽  
Jeroen Hogema ◽  
...  
Keyword(s):  
Real Time ◽  
The Road ◽  
Driver Workload ◽  
On The Road ◽  
Road Study

scholarly journals Navigating cognition: Spatial codes for human thinking

Science ◽  
2018 ◽  
Vol 362 (6415) ◽  
pp. eaat6766 ◽  
Author(s):  
Jacob L. S. Bellmund ◽  
Peter Gärdenfors ◽  
Edvard I. Moser ◽  
Christian F. Doeller
Keyword(s):  
Hippocampal Formation ◽  
Wide Spectrum ◽  
Spatial Navigation ◽  
Grid Cell ◽  
Dynamic Mapping ◽  
Mapping System ◽  
Representational Format ◽  
Orthogonal Representations ◽  
Human Thinking ◽  
And Behavior

The hippocampal formation has long been suggested to underlie both memory formation and spatial navigation. We discuss how neural mechanisms identified in spatial navigation research operate across information domains to support a wide spectrum of cognitive functions. In our framework, place and grid cell population codes provide a representational format to map variable dimensions of cognitive spaces. This highly dynamic mapping system enables rapid reorganization of codes through remapping between orthogonal representations across behavioral contexts, yielding a multitude of stable cognitive spaces at different resolutions and hierarchical levels. Action sequences result in trajectories through cognitive space, which can be simulated via sequential coding in the hippocampus. In this way, the spatial representational format of the hippocampal formation has the capacity to support flexible cognition and behavior.

scholarly journals Automatic Detection and Classification of Road, Car, and Pedestrian Using Binocular Cameras in Traffic Scenes with a Common Framework

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Yongchao Song ◽  
Jieru Yao ◽  
Yongfeng Ju ◽  
Yahong Jiang ◽  
Kai Du
Keyword(s):  
Real Time ◽  
Pedestrian Detection ◽  
Minimum Energy ◽  
Automatic Detection ◽  
Initial Contour ◽  
Target Area ◽  
Threshold Method ◽  
The Real ◽  
The Road ◽  
On The Road

In order to solve the problems of traffic object detection, fuzzification, and simplification in real traffic environment, an automatic detection and classification algorithm for roads, vehicles, and pedestrians with multiple traffic objects under the same framework is proposed. We construct the final V view through a considerate U-V view method, which determines the location of the horizon and the initial contour of the road. Road detection results are obtained through error label reclassification, omitting point reassignment, and so an. We propose a peripheral envelope algorithm to determine sources of vehicles and pedestrians on the road. The initial segmentation results are determined by the regional growth of the source point through the minimum neighbor similarity algorithm. Vehicle detection results on the road are confirmed by combining disparity and color energy minimum algorithms with the object window aspect ratio threshold method. A method of multifeature fusion is presented to obtain the pedestrian target area, and the pedestrian detection results on the road are accurately segmented by combining the disparity neighbor similarity and the minimum energy algorithm. The algorithm is tested in three datasets of Enpeda, KITTI, and Daimler; then, the corresponding results prove the efficiency and accuracy of the proposed approach. Meanwhile, the real-time analysis of the algorithm is performed, and the average time efficiency is 13 pfs, which can realize the real-time performance of the detection process.

A Picture is Worth a Thousand Words: Share Your Real-Time View on the Road

2017 ◽  
Vol 66 (4) ◽  
pp. 2902-2914 ◽  
Author(s):  
Xiong Wang ◽  
Lei Ding ◽  
Qi Wang ◽  
Jin Xie ◽  
Tianyi Wang ◽  
...  
Keyword(s):  
Real Time ◽  
The Road ◽  
On The Road

Research of Distributional Ecology Cloud-Structure

2013 ◽  
Vol 760-762 ◽  
pp. 1758-1761
Author(s):  
Ji Ming Lan ◽  
Shu Jie Lu ◽  
Li Ming Zhang
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Real Time ◽  
Service Management ◽  
Cloud Model ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Structure ◽  
Mass Data ◽  
Multiple Dimension

Proposed that idea of cloud computing ecology development, supports and guiding cloud model deployment, the cloud service management and Clouds protocols observes the purification of mix cloud environment. Has designed the multiple dimension data saving structure and real-time mass-data processing of model as well as the asynchronous overall construction distributional ecology cloud structure. It has been shown that this ecology cloud structure is healthy.

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