Conformal and Distributed Monitoring of Electromagnetic Emission Enabled by RFID Backscattering and Colorimetric Visualization
Distributed monitoring of electromagnetic radiation has emerged as a critical challenge in modern wireless environments. To address this need, we present an RFID-integrated electromagnetic field detection system that enables rapid and distributed collection of electromagnetic field intensity across the 2.2-6 GHz spectrum. The system achieves a dynamic range of 0.05 to 60 V/m for electric field monitoring while providing instantaneous visual feedback through colorimetric indicators. Validated for stable operation at bending radii exceeding 30 mm, our solution combines miniaturization, low-power operation, and mechanical flexibility to support scalable multi-node deployments. We demonstrate this capability through a 16-element multi-node prototype that simultaneously displays field intensities across distributed locations while enabling accurate RFID-based data acquisition. The system was further deployed in an automobile-manufacturing industrial scenario with 11 distributed sensing nodes, which successfully indicate potential interference sources in space and provide both immediate visual alerts and quantifiable data. The proposed sensing paradigm provides an optimized solution for spatially resolved field monitoring in industrial facilities and healthcare environments, where dense deployments of low-profile sensors are desirable for rapid identification of interference sources or mapping of overexposure zones around vulnerable populations.
Authors
- Yanhua Peng (ORCID: https://orcid.org/0000-0003-3725-1340)
- Yutong Cui (ORCID: https://orcid.org/0000-0001-5256-9299)
- Xin Yu (ORCID: https://orcid.org/0000-0002-3651-4770)
- Lingnan Song (ORCID: https://orcid.org/0000-0003-4078-1641)
- Donglin Su (ORCID: https://orcid.org/0000-0003-4395-0682)
- Yumeng Wang (ORCID: https://orcid.org/0009-0003-6105-1135)
- Z.R. Liu
Institutions
- China Automotive Technology and Research Center (CN)
- Beihang University (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-08-04
- DOI
- https://doi.org/10.1109/jsen.2025.3593496
- Primary Topic
- Knowledge Management and Technology
- Type
- article
- Field-Weighted Citation Impact
- 0.00