Multi-agent Iot-based System for Intelligent Vehicle Traffic Management Using Wireless Sensor Networks

Abstract

Aims: Integrated computing technologies such as the Internet of Things (IoT), Multi- Agent Systems (MAS), and automatic networking to deliver Internet of Vehicles (IoV) applications. Methodology: The main objective of this paper is to combine MAS with IoT or IoV a new paradigm within its Cypher Physical System (CPS) for intelligent car applications. We proposed the MAS algorithm and applied it to control traffic lights at multiple intersections. When using MAS together with scattered computing architectures, IoV can achieve higher efficiency. The proposed combination is based on the independent knowledge, adaptability, assertiveness, and responsiveness that can be used in wireless sensor paradigms to bring new remedies. Smart products will explore further advancements and diverse mobility capabilities. Results: IoT provides an appropriate atmosphere for connecting with MAS concepts and programs in addition to providing reliable, adaptable, efficient, and intelligent solutions in the automotive network. In addition, the combination of MAS with IoT and cognitive conditions could result in scalable, automated, and smart wireless sensor solutions. Conclusion: We conduct experiments on three different datasets, and the results demonstrate that MAS outperforms several state-of-the-art algorithms in alleviating traffic congestion with shorter training time.