Chipless RFID Systems Using Advanced Artificial Intelligence

Larry M. Arjomandi · Nemai Chandra Karmakar

2023-01 · Artech House

Apie šią el. knygą

This book shows you how to develop a hybrid mm-wave chipless Radio Frequency Identification (RFID) system, which includes chip-less tag, reader hardware, and detection algorithm that use image processing and machine learning (ML) techniques. It provides the background and information you need to apply the concepts of AI into detection and chip-less tag signature printable on normal plastic substrates, instead of the conventional peak/nulls in the frequency tags. You’ll learn how to incorporate new AI detection techniques along with cloud computing to lower costs. You’ll also be shown a cost-effective means of image construction, which can lower detection errors. The book focuses on side-looking-aperture-radar (SLAR) with a combination of deep learning to provide a much safer means of chipless detection than the current iSAR technique. Each chapter includes practical examples of design. With its emphasis on mm-waveband and the practical side of design and engineering of the chipless tags, reader and detection algorithms, this is an excellent resource for industry engineers, design engineers and university researchers.

Apie autorių

Larry M. Arjomandi, a current senior member of the IEEE, received his B.Sc. and M.Sc. degrees in electronics/telecommunications from Ferdowsi University of Mashhad, Iran, and a Ph.D. degree in electrical and computer science from Monash University, Australia in 2019. Previously he worked as a Research Engineer with the Amir-Kabir University Microwave Lab and Niroo Research Center, as an Information analyzer with Tehran Stock Exchange, and as a Radio Optimization manager with Ericsson. Currently he is a sessional Senior Research Engineer in embedded systems at Swinburne University, and a Senior System Engineer at Transport Certification Australia. Dr. Arjomandi received the PARC US Research Associate award, Palo-Alto, California in 2018 and has two translated books, a few national and international papers, and two international patents. His current research interests include chipless RFID, image-processing techniques, and real-life applications of machine learning.

Nemai Chandra Karmakar, a current senior member of the IEEE, obtained his B.Sc (EEE) and M.Sc (EEE) from Bangladesh University of Engineering and Technology, Dhaka, his M.Sc. degree in Electrical Engineering from the University of Saskatchewan, Saskatoon, Canada, his PhD degree from the University of Queensland, Brisbane, Australia in 1999, Postgraduate Diploma in Teaching in Higher Education from The National Institute of Education, Nanyang Technological University, Singapore and Master in Higher Education from Griffith University, Australia. Previously, he worked as an Assistant Engineer in Electronics Institute, Atomic Energy Research Establishment, Dhaka, Bangladesh, a Research Assistant at the Communications Research Group, University of Saskatchewan, Canada, as a Microwave Design Engineer at Mitec Ltd., Brisbane, Australia where he contributed to the development of land mobile satellite antennas for the Australian Mobilesat. Dr. Karmakar currently works in the Faculty of Engineering at Monash University as an Associate Professor within the department of Electrical and Computer Systems Engineering and he is the director of Monash Microwave, Antennas, RFID and Sensors (MMARS) Lab.