Title: Internet of vehicle things communication based on big data analytics integrated internet of things

Authors: Ruiwei Chen; Bala Anand Muthu

Addresses: Xinyang Vocational and Technical College, Xinyang 464100, China ' Department of Computer Science & Engineering, Adhiyamaan College of Engineering, Hosur, India

Abstract: Automobile industries' rapid development on modern wireless vehicle communication among vehicles, pedestrians, and roadside information units has been termed the Internet of Vehicles (IoV). The significant challenges of the IoV include vehicle data management and congestion in the network. In this research, Big Data analytics integrated the IoT framework (BDA-IoTF) is proposed to process the data received from the roadside units to minimise congestion and optimised data management. Further, the vehicle data has been analysed for several conditions that help to analyse the network congestion. Based on the congestion level, BDA-IoTF helps evaluate the vehicles' performance in correlation with data management. This Big Data analytics gives immense support in segregation, management, and data collection based on IoT, by sending data directly to the database using wireless radio frequency technology. The proposed BDA-IoTF has been validated based on the optimisation parameter, which outperforms conventional methods. Thus the experimental results show the BDA-IoTF improve vehicle data management (96.2%) and minimising the traffic congestion (21.4%) with high performance (95.6%), accuracy (98.2%), and error rate (16.7%), efficiency (93.8%), transportation optimisation (94.1%), delay time (18.5%) when compared to other methods.

Keywords: internet of things; internet of vehicles; roadside unit; sensors; big data analytics; congestion.

DOI: 10.1504/IJIPT.2022.125970

International Journal of Internet Protocol Technology, 2022 Vol.15 No.3/4, pp.203 - 213

Received: 16 Apr 2021
Accepted: 03 Jun 2021

Published online: 05 Oct 2022 *

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