Real-time prediction of accident using Big data system

被引：1
|
作者：
Tantaoui, Mouad [1 ]
Laanaoui, My Driss [2 ]
Kabil, Mustapha [3 ]
机构：
[1] Univ Hassan II Casablanca, Math & Applicat Lab, Casablanca, Morocco
[2] Univ CADI AYYAD Marrakesh, Lab Math & Comp Sci, Marrakech, Morocco
[3] Univ Hassan II Casa, Lab Appl Math & Applicat, Casablanca, Morocco
来源：
3RD INTERNATIONAL CONFERENCE ON NETWORKING, INFORMATION SYSTEM & SECURITY (NISS'20) | 2020年
关键词：
VANET; Big Data; Traffic density; Lambda architecture;
D O I：
10.1145/3386723.3387886
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we propose a new prediction system in real time using Big Data to improve the VANET network. Firstly, The Traffic density and average speed are calculated in each section of road, and then the risk of vehicle accident is predicted in instantaneous manner with parallel data processing, which makes execution faster.
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页数：5
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