Predictive Modeling of Work-Rest Schedule for Agricultural Workers Using Heat Stress and Physiological Data.

Abstract

OCCUPATIONAL APPLICATIONSThis study provides practical, field-tested predictive tools to schedule work and rest in hot agricultural settings. Using routinely measured inputs (wet-bulb globe temperature [WBGT], heart-rate metrics, age, mechanization status, and simple lifestyle indicators), practitioners and supervisors can estimate safe continuous work durations and the necessary recovery periods for individual workers. Applicable to smallholder and mechanized tillage operations, these models support on-site decision-making to reduce heat-related fatigue, minimize injury risk, and maintain productivity. The models can be integrated into supervisor checklists, simple mobile apps, or wearable-sensor dashboards to immediately improve heat-stress management policies and worker scheduling.