Next-generation IoT: harnessing AI for enhanced localization and energy harvesting in backscatter communications

Nesbitt, R., Shah, S. T. , Wagih, M. , Imran, M. A. , Abbasi, Q. H. and Ansari, S. (2023) Next-generation IoT: harnessing AI for enhanced localization and energy harvesting in backscatter communications. Electronics, 12(24), 5020. (doi: 10.3390/electronics12245020)

Abstract

Ongoing backscatter communications and localisation research have been able to obtain incredibly accurate results in controlled environments. The main issue with these systems is faced in complex RF environments. This paper investigates concurrent localization and ambient radio frequency (RF) energy harvesting using backscatter communication systems for Internet of Things networks. Dynamic real-world environments introduce complexity from multipath reflection and shadowing, as well as interference from movements. A machine learning framework leveraging K-Nearest Neighbors and Random Forest classifiers creates robustness against such variability. Historically, received signal measurements construct a location fingerprint database resilient to perturbations. The Random Forest model demonstrates precise localization across customized benches with programmable shuffling of chairs outfitted with RF identification tags. Average precision accuracy exceeds 99% despite deliberate placement modifications, inducing signal fluctuations emulating mobility and clutter. Significantly, directional antennas can harvest over −3 dBm, while even omnidirectional antennas provide −10 dBm—both suitable for perpetually replenishing low-energy electronics. Consequently, the intelligent backscatter platform localizes unmodified objects to customizable precision while promoting self-sustainability.

• Item Type: Articles
• Keywords: RFID, backscatter, RF energy harvesting, 6G, IoT, machine learning, localisation.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Shah, Dr Syed Tariq and Nesbitt, Mr Rory and Ansari, Dr Shuja and Imran, Professor Muhammad and Wagih, Dr Mahmoud and Abbasi, Professor Qammer

Creator Roles

Nesbitt, R.: Conceptualization, Methodology, Software, Validation, Writing – original draft
Wagih, M.: Conceptualization, Data curation, Writing – review and editing
Ansari, S.: Conceptualization, Formal analysis, Writing – review and editing, Supervision
Shah, S. T.: Methodology, Validation, Software, Formal analysis, Investigation, Data curation, Writing – review and editing, Supervision
Imran, M.: Methodology, Writing – review and editing, Supervision
Abbasi, Q.: Investigation, Writing – review and editing, Supervision

• Authors: Nesbitt, R., Shah, S. T., Wagih, M., Imran, M. A., Abbasi, Q. H., and Ansari, S.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity; College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: Electronics
• Publisher: MDPI
• ISSN: 2079-9292
• ISSN (Online): 2079-9292
• Published Online: 15 December 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Electronics 12(24):5020
• Publisher Policy: Reproduced under a Creative Commons license