Machine learning based accident prediction in secure IoT enable transportation system

被引:42
作者
Mohanta, Bhabendu Kumar [1 ]
Jena, Debasish [2 ]
Mohapatra, Niva [2 ]
Ramasubbareddy, Somula [3 ]
Rawal, Bharat S. [4 ]
机构
[1] Centurion Univ Technol & Management, Dept CSE, Bhubaneswar 752050, Odisha, India
[2] Int Inst Informat Technol, Dept CSE, Bhubaneswar, Odisha, India
[3] VNRVJIET, Dept Informat Technol, Hyderabad, India
[4] Gannon Univ, Dept Cybersecur, Erie, PA USA
关键词
Intelligent data analytics; machine learning; intelligent transportation system; secure communication; internet of things; SEVERITY PREDICTION;
D O I
10.3233/JIFS-189743
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Smart city has come a long way since the development of emerging technology like Information and communications technology (ICT), Internet of Things (IoT), Machine Learning (ML), Block chain and Artificial Intelligence. The Intelligent Transportation System (ITS) is an important application in a rapidly growing smart city. Prediction of the automotive accident severity plays a very crucial role in the smart transportation system. The main motive behind this research is to determine the specific features which could affect vehicle accident severity. In this paper, some of the classification models, specifically Logistic Regression, Artificial Neural network, Decision Tree, K-Nearest Neighbors, and Random Forest have been implemented for predicting the accident severity. All the models have been verified, and the experimental results prove that these classification models have attained considerable accuracy. The paper also explained a secure communication architecture model for secure information exchange among all the components associated with the ITS. Finally paper implemented web base Message alert system which will be used for alert the users through smart IoT devices.
引用
收藏
页码:713 / 725
页数:13
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