Artificial intelligence based on fuzzy logic for a long-range radio frequency identification reader antenna

Abstract

The radiation pattern of radio frequency identification (RFID) antennas is influenced by various factors such as design, operating frequency, and polarization, which determine characteristics like directionality, omnidirectionality, beam width, and gain. Achieving precise readings over extended distances is crucial for the effectiveness of RFID systems, enabling faster item retrieval and delivery. The read distance, a critical aspect of RFID system performance, depends on factors like transmitted power, frequency, and antenna gain. Passive backscatter RFID setups particularly benefit from optimizing read distance for efficient operation. Fuzzy logic, as a soft computing technique, addresses uncertainties inherent in RFID systems effectively. This paper presents a novel approach to RFID antenna design, utilizing fuzzy logic to dynamically adjust frequency and power transmission. By enhancing field distribution, polarization, and received signal strength, this approach aims to optimize tag readings at extended distances, thereby improving overall system effectiveness. The methodology involves implementing algorithms in a C program to control the long-range distance aspects of the RFID system. Incorporating fuzzy rule algorithms into the RFID system's control logic enhances its ability to respond intelligently to changes in the operating environment, contributing to improved performance and reliability in long-range RFID applications.