RFID-based location based services framework for alerting on black spots for accident prevention

被引:3
作者
Ochieng, Wilson Ogutu [1 ]
Cheruiyot, Kipruto Wilson [1 ]
Okeyo, George [1 ]
机构
[1] Jomo Kenyatta Univ Agr & Technol, Nairobi, Kenya
关键词
Transportation; M-RFID; GPS; LBS; Black spot; Exposure; Likelihood; Impact;
D O I
10.1016/j.eij.2021.06.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The need of developing systems that address traffic matters such as traffic control and accidents has led to the development of a number of techniques, methods and tools to address road usability issues. Many automated models have been proposed and applied in different scenarios such as road oddities. Despite of the advantages of these models the major problem of road accidents continue to pose problem glob-ally. This has created the need to come up with more user-effective approaches to address road accidents. Main objective of this research therefore is to identify and address the gap in Location Based Services (LBS). A model that combines RFID and GPS technology to provide Location Based Services via audio alerts to drivers as they approach black spots is presented. The model provides location based services to dri-vers as they approach black spots causing them to adjust their driving accordingly (i.e. speeding, overtak-ing). Since LBS technologies have different limitations, most researchers have focused on addressing accuracy limitation by proposing hybrid technologies. Accuracy requirement varies depending on appli-cation area. The analysis of the different technologies revealed that in vehicle transportation medium accuracy is effective. This research focused on availability aspect which is a key requirement in LBS. To achieve this a model made up of RFID & GPS is formulated. Higher availability of significant alerts at black spots is registered through simulation as compared to alerts when the technologies are applied sepa-rately. Black spot accidents are therefore managed due to safer driving around black spots. This can lead to reduction in exposure to accidents, likelihood of occurrence and impact in the event of an incident. Usability metrics is used to determine effectiveness of the model. (c) 2022 THE AUTHORS. Published by Elsevier B.V. on behalf of Faculty of Computers and Information, Cairo University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:65 / 72
页数:8
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