The potential of Personal Comfort Systems (PCS) in outdoor applications, particularly their short-term efficacy in cold environments, is pivotal for enhancing thermo-physiological safety among sanitation workers. Our study evaluated four heating modalities—Continuous Heating (CH), Continuous Heating under Windproof Tent (CHW), Intermittent Heating (IH), and Intermittent Heating under Windproof Tent (IHW)—to determine their impact on thermal-physiological responses in winter conditions. We constructed initial temperature response models to refine PCS performance, yielding four key insights: 1) Thermal sensation vote (TSV), Thermal comfort vote (TCV), and Local thermal sensation vote (LTSV) varied across heating modes, with CH and CHW eliciting greater increases than IH and IHW. 2) Chest skin temperature rose consistently during personalized heating, whereas upper arm and lower calf skin temperatures were influenced by the integrated thermal environment. 3) Personalized adjustments led to optimal heating states, with CHW achieving the highest mean final heating temperature at waist, buttocks, and thighs, and CH at the upper back. 4) Machine learning algorithms, particularly Random Forest Regression models, were instrumental in developing predictive models, demonstrating high accuracy (R2 > 0.9) for initial temperature optimization.
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