MIRO: Multi-radar Identity and Ranging for Occupational Safety
This system provides a privacy-preserving solution for worker-specific PM exposure estimation, which is crucial for occupational safety in industrial environments, addressing limitations of existing monitoring solutions.
This paper addresses the challenge of monitoring occupational exposure to airborne particulate matter (PM) in industrial workspaces. They developed MIRO, a system that integrates PM sensing with a multi-radar millimeter-wave re-identification backbone, achieving a re-ID F1-score of 90.4% and a mean Structural Similarity Index Measure (SSIM) of 0.70 for view adaptation accuracy in lab experiments.
Occupational exposure to airborne particulate matter (PM) poses a severe health risk in open industrial workspaces such as stonecutting yards. Conventional monitoring solutions such as wearable PM sensors and camera-based tracking are impractical due to discomfort, maintenance issues, and privacy concerns. We present MIRO, a privacy-preserving framework that integrates continuous PM sensing with a multi-radar millimeter-wave (mmWave) re-identification (re-ID) backbone. A distributed network of PM sensors captures localized pollutant concentrations, while spatially overlapping mmWave radars track and re-associate workers across viewpoints without relying on visual cues. To ensure identity consistency across radars, we introduce a GAN-based view adaptation network that compensates for azimuthal distortions in range-Doppler (RD) signatures, combined with correlation-based cross-radar matching. In controlled laboratory experiments, our system achieves a re-ID F1-score of 90.4% and a mean Structural Similarity Index Measure (SSIM) of 0.70 for view adaptation accuracy. Field trials in rural stone-cutting yards further validate the system's robustness, demonstrating reliable worker-specific PM exposure estimation.