AI-Optimized Micro strip Antennas for Enhanced Vehicular Communication Systems

The application of artificial intelligence (AI) in designing micro-strip antennas has a great effect on car communication applications. Modern vehicles use the most efficient and latest cutting-edge wireless communication systems—such as V2V (vehicle-to-vehicle) and V2I (vehicle-to-infrastructure) networks—so there is a great need for small, high-performance antennas. The traditional methods of design often find it challenging to manage the factors of gain, bandwidth, and radiation efficiency, which are the basic elements of a progressive driving environment that requires seamless connectivity. This paper presents the use of AI optimization techniques such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Deep Learning (DL) to improve the antenna design in vehicular communication systems. Through AI-based processes, the antennas that are more efficient, for example, interference reduction and signal strength enhancement, as well as those with a smaller size, enable better and more reliable communication for intelligent transportation systems (ITS). The finding of the research shows that the micro-strip antennas which are AI-based can enhance network performance in vehicles to the great extent; these antennas can be used in, for instance, autonomous driving, traffic management, and real-time data exchange.