A passive internet of things environment physical quantity signal identification method and electronic equipment
By combining metamaterial tags and machine learning models, collaborative sensing and decoupling of multiple physical quantities in a passive IoT environment is achieved, solving the problems of high power consumption and complex operation in existing technologies, and realizing accurate identification with low power consumption.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUAZHONG UNIV OF SCI & TECH
- Filing Date
- 2026-04-03
- Publication Date
- 2026-07-17
AI Technical Summary
Existing passive IoT environmental physical quantity identification methods are difficult to achieve collaborative sensing of multiple environmental physical quantities, and have high power consumption, complex operation, and cannot effectively separate and analyze multi-path scattered signals.
Metamaterial tags are used to sense environmental physical quantities in real time, and channel estimation is performed by pilot sequences in backscattered signals. The reflection coefficient is iteratively corrected by combining machine learning models to construct an equivalent channel matrix, thereby achieving collaborative sensing and decoupling of multiple environmental physical quantities.
It achieves accurate collaborative sensing of multiple environmental physical quantities under low power consumption, simplifies the operation process, improves the stability and robustness of signal analysis, and reduces computational overhead.
Smart Images
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