Speech-Controlled Reconfigurable Intelligent Metasurface for Real-Time Wireless Power Transfer and Communication

  • Lin Dong
  • , Liming Si*
  • , Yueze Liu
  • , Qitao Shen
  • , Pengcheng Tang
  • , Genhao Wu
  • , Rong Niu
  • , Qingqing Wu
  • , Weiren Zhu*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

As the Internet of Things (IoT) continues to evolve, a growing number of wireless sensors have been integrated into daily life, posing new challenges to energy supply and communication. Point-to-point dynamic wireless power transfer and communication, enabled by user-based positioning and tracking services, hold great potential in the IoT. Here, we propose a speech-controlled reconfigurable intelligent metasurface (RIS) that translates natural-language commands into dynamically shaped electromagnetic beams by combining speech interaction, low-power RIS control, and a template matching algorithm, supporting real-time data communication and wireless power transfer for both static and moving targets. Unlike conventional RISs that rely on pre-defined control and external processing units, our approach provides the metasurface with visual and linguistic perception capabilities, enabling a paradigm shift from passive reconfiguration to active multimodal intelligence. The experimental results confirm the effectiveness of the speech-controlled RIS, while the measured results demonstrate that the RIS can provide a stable dc output that exceeds 4.61 V on dynamic targets. By enabling intuitive human–device interaction and effectively meeting the power supply requirements of small sensors, the proposed concept demonstrates strong application potential in IoT scenarios.

Original languageEnglish
Article number0831
JournalResearch
Volume8
DOIs
Publication statusPublished - 2025

Fingerprint

Dive into the research topics of 'Speech-Controlled Reconfigurable Intelligent Metasurface for Real-Time Wireless Power Transfer and Communication'. Together they form a unique fingerprint.

Cite this