Performance analysis of vehicle-to-everything communication using internet of LoRa computing for intelligent transportation system

Abstract

Intelligent Transportation System (ITS) is an emerging field nowadays that is widely utilized to improve safety measures, avoid abnormalities, and traffic flow control, and also develops the environment without hassle. So far, the deployment of sensors into vehicles and the analyzing the vehicular parameters towards the smart city applications have been achieved by the integration of LoRa-based vehicular communication. However, trust in previous design architecture should need efficient transmission, robustness, and energy efficiency. To overcome the challenges, the proposed system designed the Internet of LoRa computing enabled vehicular communication with high reliability by offering the optimization technique namely an Enhanced Artificial Bee Colony (EABC) algorithm for the localization scheme. The proposed framework consists of two sections. First, observe the objects nearby vehicles using an ultrasonic sensor that is equipped in the Arduino module with a LoRa shield. The second work contributes to the evaluation of performance metrics of vehicular communication in the sensing region with a minimum delay of two seconds using MathWorks simulation. The article designed the VANET, which utilized the LoRa architecture for Vehicle to Everything communication, and pointed out the position of the sensor nodes using a localization scheme (EABC algorithm), comparing the proposed EABC algorithm with the other optimization techniques viz Particle Swarm Optimization and Genetic algorithms in the dense nodes and it achieves 25% variation in minimizing the position error at a certain speed. Further, find the system performance by calculating the BER (Bit Error Rate) in both coherent and non-coherent with varying speeds of the vehicle and router connections and it achieves 40% variation in efficiency and realizes the network coverage in terms of the position of the vehicle in the way the proposed framework achieves the high accuracy in overall system throughput.