MIRO: Multi-radar Identity and Ranging for Occupational Safety
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866910045209362432 |
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| author | Halder, Tirthankar Sen, Argha Pradhan, Swadhin Sen, Rijurekha Chakraborty, Sandip |
| author_facet | Halder, Tirthankar Sen, Argha Pradhan, Swadhin Sen, Rijurekha Chakraborty, Sandip |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_07531 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | MIRO: Multi-radar Identity and Ranging for Occupational Safety Halder, Tirthankar Sen, Argha Pradhan, Swadhin Sen, Rijurekha Chakraborty, Sandip Human-Computer Interaction 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. |
| title | MIRO: Multi-radar Identity and Ranging for Occupational Safety |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2603.07531 |