Adaptive Smart Traffic Accidents Management System
Dublin Core
Title
Adaptive Smart Traffic Accidents Management System
Subject
Clustering
Cupcarbon
IoT
WSN
5G
Description
The proliferation of smart devices, IoT applications and wireless communication technologies contribute in countries development, society’s security, cost reduction, and customer services satisfactions; since they are used in different aspects of our life. Traffic congestion and accidents are increased recently and reached critical limits, so these contribute in initiating sever problems for researchers, governments and industry over the last few decades. Traffic accidents have many defects relating to increase number of death, infrastructure distribution, and health injuries; therefore, there is a crucial need to develop and modify an approach that utilizes the new technology to limit and prevent the traffic accidents. Wireless sensors networks are developed to support smart solutions in smart cities like smart traffic, smart grid and others. In this research we developed a comprehensive approach to achieve the following three important goals in smart accident elimination. The first goal is to minimize the number of exchange information packets between sensors to save the battery life through developing and adapting clustering schema to minimize the number of exchanges information packets. The second goal is to calculate and determine the optimum route from accident location to the nearest rescue location by developing a dynamic routing schema that is calculated by the control station depending on a cost heuristics function. The third goal is to predicate the accident causes and minimize the probability of accidents occur using a warning message schema and drawing some obstacles on some routing paths. Cupcarbon simulator and MATLAB software tool are developed to simulate different scenarios in order to proof the research goals.
Creator
Alzyoud, Faisal Yousef
Alnuaimi, Abdallah Altahan
Al Shrouf, Faiz
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 14 (2021); pp. 72-89
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2021-07-28
Rights
Copyright (c) 2021 Faisal yousef Alzyoud
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Faisal Alzyoud Yousef, Abdallah Alnuaimi Altahan and Al Shrouf, Faiz, Adaptive Smart Traffic Accidents Management System, International Association of Online Engineering (IAOE), Vienna, Austria, 2021, accessed November 22, 2024, https://igi.indrastra.com/items/show/1882