An Effective Tag Estimation Method Based upon Artificial Neural Networks and Signal Strength for Anticollision in Radio Frequency Identification Systems

• DOI: 10.1007/s44196-024-00587-5
• Publication Date: 2024-08-05T06:02:40Z
• Authors: Shakir A. H. Alhu...; Mohsin Murad; Imran A. Tasadduq; Mohammad Hamza Awedh; Ali M. Rushdi; Sultan Alotaibi
• Keywords: Signal strength; SIGNAL (programming language); Identification

Abstract Radio frequency identification (RFID) technology has been widely used in applications such as access control, inventory management, spatial positioning, and object identification. Accurate tag estimation is one of the major challenges RFID reader systems particularly areas where large populations are to be identified shopping carts, warehouse monitoring, small ruminant farms. This paper proposes a new technique employing artificial neural networks (ANNs) signal strength read populations. The estimates number tags through backscatter channel for efficient implementation dynamic framed slotted Aloha (DFSA) protocol by analyzing RN16 received indicator (RSSI). ANN model trained using various can identify with minimal errors. proposed does not require any modification implemented software script added module reader. strength-ANN able estimate accurate thereby improving performance employed DFSA model.