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<p>Intelligent devices have significantly improved our daily lives, but have engendered security and privacy concerns. To mitigate these issues, a real-time intelligent sensing system with privacy protection is proposed based on a space-time-coding metasurface antenna. The employed metasurface antenna has a low profile, fast programmability, and flexible wavefront reconfiguration capability, enabling single-beam steering across a ±60° range with 15° resolution over distances of 0.6.2 m. Through rapid beam steering, timely signal processing, and synchronization optimization, the system achieves precise and real-time target tracking with an ultralow latency of 0.01 s. Crucially, the system is configured to solely detect the presence and movement of individuals without capturing visual images, thus avoiding the privacy risks inherent in video surveillance. This research holds great potential for advancement in smart homes, healthcare systems, and cognitive radars, providing a viable solution to alleviate visual privacy concerns.</p>

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Enhanced real-time intelligent sensing with privacy protection by a compact space-time-coding metasurface antenna

  • 期刊论文

  • 发表日期：

    2025年9月11日

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  • Huiming Yao,
  • Baiying Taishi,
  • Jiaxin Li,
  • Jianchun Xu,
  • Kai Huang,
  • Ke Bi

摘要

Intelligent devices have significantly improved our daily lives, but have engendered security and privacy concerns. To mitigate these issues, a real-time intelligent sensing system with privacy protection is proposed based on a space-time-coding metasurface antenna. The employed metasurface antenna has a low profile, fast programmability, and flexible wavefront reconfiguration capability, enabling single-beam steering across a ±60° range with 15° resolution over distances of 0.6.2 m. Through rapid beam steering, timely signal processing, and synchronization optimization, the system achieves precise and real-time target tracking with an ultralow latency of 0.01 s. Crucially, the system is configured to solely detect the presence and movement of individuals without capturing visual images, thus avoiding the privacy risks inherent in video surveillance. This research holds great potential for advancement in smart homes, healthcare systems, and cognitive radars, providing a viable solution to alleviate visual privacy concerns.