Integrating AI and Environmental Analytics for Enhanced Productivity and Safety

Abstract

In the modern workplace, managing outdoor work schedules has become increasingly challenging due to unpredictable weather conditions. This paper presents an innovative solution that combines real-time weather forecasts with Artificial Intelligence (AI) to create adaptive work schedules. By integrating data from reliable weather sources and analyzing it using machine learning models, we can predict the optimal times for outdoor work, reducing health risks and enhancing productivity. Additionally, we explore the use of the Wet Bulb Globe Temperature (WBGT) index to assess the risk of heat stress and adjust work hours accordingly. Our approach incorporates a dynamic scheduling algorithm that considers factors such as legal work hour limits and the intensity of physical labor. The result is a flexible, AI-powered system that not only ensures worker safety in the face of heat stress but also helps organizations navigate the complexities of climate impact on workforce management. Through this study, our goal is to demonstrate how technology can be leveraged to support a safer and more efficient working environment.